{"670238":{"#nid":"670238","#data":{"type":"event","title":"Michael Mitzenmacher (Klaus 1116, 11am)","body":[{"value":"\u003Cp\u003EMichael Mitzenmacher (Harvard), Algorithms with Predictions\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EAbstract: We survey the recent introduction of and advances in algorithms that use predictions applied to the input, such as from machine learning, to circumvent worst-case analysis. We aim for algorithms that have near optimal performance when these predictions are good, but still maintain provable bounds (such as for worst-case performance) even when the predictions have large errors. We look at several examples showing how predictions can be used effectively while still allowing for theoretical guarantees, covering our own work in scheduling and Bloom filter data structures,\u0026nbsp;as well as several other recent\u0026nbsp;results.\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\nBio: Michael Mitzenmacher is a Professor of Computer Science in the School of Engineering and Applied Sciences at Harvard University. Michael has authored or co-authored over 250 conference and journal publications on a variety of topics, including algorithms for the Internet, efficient hash-based data structures, erasure and error-correcting codes, power laws, and compression. He is an ACM and IEEE Fellow. He has co-authored a widely used textbook on randomized algorithms and probabilistic techniques in computer science published by Cambridge University Press.\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EMichael Mitzenmacher (Harvard), Algorithms with Predictions\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EAbstract: We survey the recent introduction of and advances in algorithms that use predictions applied to the input, such as from machine learning, to circumvent worst-case analysis. We aim for algorithms that have near optimal performance when these predictions are good, but still maintain provable bounds (such as for worst-case performance) even when the predictions have large errors. We look at several examples showing how predictions can be used effectively while still allowing for theoretical guarantees, covering our own work in scheduling and Bloom filter data structures,\u0026nbsp;as well as several other recent\u0026nbsp;results.\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\nBio: Michael Mitzenmacher is a Professor of Computer Science in the School of Engineering and Applied Sciences at Harvard University. Michael has authored or co-authored over 250 conference and journal publications on a variety of topics, including algorithms for the Internet, efficient hash-based data structures, erasure and error-correcting codes, power laws, and compression. He is an ACM and IEEE Fellow. He has co-authored a widely used textbook on randomized algorithms and probabilistic techniques in computer science published by Cambridge University Press.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"ARC Colloquium: Algorithms with Predictions"}],"uid":"36512","created_gmt":"2023-10-06 12:07:30","changed_gmt":"2023-10-31 19:29:40","author":"wperkins3","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-11-06T11:00:00-05:00","event_time_end":"2023-11-06T12:00:00-05:00","event_time_end_last":"2023-11-06T12:00:00-05:00","gmt_time_start":"2023-11-06 16:00:00","gmt_time_end":"2023-11-06 17:00:00","gmt_time_end_last":"2023-11-06 17:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Klaus 1116","extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"670235":{"#nid":"670235","#data":{"type":"event","title":"Thomas Rothvoss Lectures on Integer Programming","body":[{"value":"\u003Cp\u003EWednesday October 18, 11am-12pm, Klaus 1116:\u0026nbsp; Introduction to Lattices;\u0026nbsp;\u0026nbsp;\u003Cbr \/\u003E\r\n---\u003Cbr \/\u003E\r\nIn this lecture, we will give a brief introduction to the lattices and discuss the seminal result\u003Cbr \/\u003E\r\nof Micciancio and Voulgaris (2010) that gives a 2^O(n) time algorithm for computing a closest vector.\u003Cbr \/\u003E\r\nWe will also discuss the result by Dadush and Vempala (2012) to enumerate all the lattice points\u003Cbr \/\u003E\r\nin a general convex body K in time 2^O(n) times the maximum number of points that any translate may contain.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cbr \/\u003E\r\nThursday October 19, 11am-12pm Klaus 2447: The Reverse Minkowski Theorem\u003C\/p\u003E\r\n\r\n\u003Cp\u003E---\u003Cbr \/\u003E\r\nWe explain the Reverse Minkowski Theorem due to Regev and Stephens-Davidowitz (2017). Formally the\u003Cbr \/\u003E\r\nresult states that for any lattice Lambda that does not contain a sublattice of determinant less than 1,\u003Cbr \/\u003E\r\nthe sum of Gaussian weights satisfies rho_1\/t(Lambda) \u0026lt;= 3\/2 where t = Theta(log n).\u003Cbr \/\u003E\r\nIn particular this implies that, any such lattice contains at most a quasi-polynomial number of vectors of length at most O(1).\u003Cbr \/\u003E\r\nThe result is based on advanced concepts from convex geometry.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cbr \/\u003E\r\nFriday October 20, 1pm-2pm, Skiles 005: The Subspace Flatness Conjecture and Faster Integer Programming\u003C\/p\u003E\r\n\r\n\u003Cp\u003E---\u003Cbr \/\u003E\r\nIn a seminal paper, Kannan and Lov\u00e1sz (1988) considered a quantity \u03bc_KL(\u039b,K) which denotes the best volume-based\u003Cbr \/\u003E\r\nlower bound on the covering radius \u03bc(\u039b,K) of a convex body K with respect to a lattice \u039b.\u003Cbr \/\u003E\r\nKannan and Lov\u00e1sz proved that \u03bc(\u039b,K)\u2264n\u22c5\u03bc_KL(\u039b,K) and the Subspace Flatness Conjecture by Dadush (2012) claims a O(log(n)) factor suffices,\u003Cbr \/\u003E\r\nwhich would match the lower bound from the work of Kannan and Lov\u00e1sz.\u003Cbr \/\u003E\r\nWe settle this conjecture up to a constant in the exponent by proving that \u03bc(\u039b,K)\u2264O(log^3(n))\u22c5\u03bc_KL(\u039b,K).\u003Cbr \/\u003E\r\nOur proof is based on the Reverse Minkowski Theorem due to Regev and Stephens-Davidowitz (2017).\u003Cbr \/\u003E\r\nFollowing the work of Dadush (2012, 2019), we obtain a (log(n))^O(n)-time randomized algorithm to solve\u003Cbr \/\u003E\r\ninteger programs in n variables. Another implication of our main result is a near-optimal flatness constant of O(n*log^3(n)).\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EPart 1 - Introduction to Lattices\u003Cbr \/\u003E\r\nPart 2 - The Reverse Minkowski Theorem\u003Cbr \/\u003E\r\nPart 3 - The Subspace Flatness Conjecture and Faster Integer Programming\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Special ARC Lecture Series"}],"uid":"36512","created_gmt":"2023-10-06 11:54:08","changed_gmt":"2023-10-12 13:57:19","author":"wperkins3","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-10-18T07:49:31-04:00","event_time_end":"2023-10-20T08:49:31-04:00","event_time_end_last":"2023-10-20T08:49:31-04:00","gmt_time_start":"2023-10-18 11:49:31","gmt_time_end":"2023-10-20 12:49:31","gmt_time_end_last":"2023-10-20 12:49:31","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"670240":{"#nid":"670240","#data":{"type":"event","title":"Jakob Moosbauer (Klaus 1116, 11am)","body":[{"value":"\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cstrong\u003E\u003Cspan\u003E\u003Cspan\u003EJakob Moosbauer (Johannes Kepler University), talk title TBA\u003C\/span\u003E\u003C\/span\u003E\u003C\/strong\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003Etalk title TBA\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"ARC Colloquium"}],"uid":"36512","created_gmt":"2023-10-06 12:19:04","changed_gmt":"2023-10-06 12:19:04","author":"wperkins3","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-11-27T11:00:00-05:00","event_time_end":"2023-11-27T12:00:00-05:00","event_time_end_last":"2023-11-27T12:00:00-05:00","gmt_time_start":"2023-11-27 16:00:00","gmt_time_end":"2023-11-27 17:00:00","gmt_time_end_last":"2023-11-27 17:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Klaus 1116","extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"670239":{"#nid":"670239","#data":{"type":"event","title":"Ruoqi Shen (Klaus 1116, 11am)","body":[{"value":"\u003Cp\u003ERuoqi Shen (Washington)\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003Etalk title TBA\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"ARC Colloquium"}],"uid":"36512","created_gmt":"2023-10-06 12:13:01","changed_gmt":"2023-10-06 12:13:01","author":"wperkins3","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-11-13T11:00:00-05:00","event_time_end":"2023-11-13T12:00:00-05:00","event_time_end_last":"2023-11-13T12:00:00-05:00","gmt_time_start":"2023-11-13 16:00:00","gmt_time_end":"2023-11-13 17:00:00","gmt_time_end_last":"2023-11-13 17:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Klaus 1116","extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"670237":{"#nid":"670237","#data":{"type":"event","title":"Mitali Bafna (Klaus 1116, 11am)","body":[{"value":"\u003Cp\u003EMitali Bafna (MIT), talk title TBA\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003Etalk title TBA\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"ARC Colloquium"}],"uid":"36512","created_gmt":"2023-10-06 12:03:49","changed_gmt":"2023-10-06 12:09:52","author":"wperkins3","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-10-30T11:00:00-04:00","event_time_end":"2023-10-30T12:00:00-04:00","event_time_end_last":"2023-10-30T12:00:00-04:00","gmt_time_start":"2023-10-30 15:00:00","gmt_time_end":"2023-10-30 16:00:00","gmt_time_end_last":"2023-10-30 16:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Klaus 1116","extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"670236":{"#nid":"670236","#data":{"type":"event","title":"Shyam Narayanan (Klaus 1116, 11am)","body":[{"value":"\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cstrong\u003E\u003Cspan\u003E\u003Cspan\u003EShyam Narayanan\u003C\/span\u003E\u003C\/span\u003E\u003C\/strong\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E \u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E(MIT) talk title TBA\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003Etalk title TBA\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"ARC Colloquium"}],"uid":"36512","created_gmt":"2023-10-06 12:00:18","changed_gmt":"2023-10-06 12:09:30","author":"wperkins3","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-10-23T11:00:00-04:00","event_time_end":"2023-10-23T12:00:00-04:00","event_time_end_last":"2023-10-23T12:00:00-04:00","gmt_time_start":"2023-10-23 15:00:00","gmt_time_end":"2023-10-23 16:00:00","gmt_time_end_last":"2023-10-23 16:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Klaus 1116","extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"670234":{"#nid":"670234","#data":{"type":"event","title":"Rahul Ilango (Klaus 1116, 11am)","body":[{"value":"\u003Cp\u003ERahul Ilango; talk title TBA\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003Etalk title TBA\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"ARC Colloquium"}],"uid":"36512","created_gmt":"2023-10-06 11:49:08","changed_gmt":"2023-10-06 12:08:30","author":"wperkins3","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-10-16T11:00:00-04:00","event_time_end":"2023-10-16T12:00:00-04:00","event_time_end_last":"2023-10-16T12:00:00-04:00","gmt_time_start":"2023-10-16 15:00:00","gmt_time_end":"2023-10-16 16:00:00","gmt_time_end_last":"2023-10-16 16:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Klaus 1116","extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"669707":{"#nid":"669707","#data":{"type":"event","title":"ARC Colloquium: June Vuong (Klaus 1116, 11am)","body":[{"value":"\u003Cp\u003EJune Vuong (Stanford)\u003C\/p\u003E\r\n\r\n\u003Cp\u003ETitle: Tight Markov chain analysis using discrete log-concavity\u003C\/p\u003E\r\n\r\n\u003Cp\u003EAbstract:\u003C\/p\u003E\r\n\r\n\u003Cp\u003ESampling is a fundamental task with many applications in algorithm design and in machine learning. Sampling from high-dimensional discrete distributions, such as Ising models, has long been studied for its applications in statistical physics, image modeling, and neural networks, as well as its connection to complexity theory. While Markov chain Monte Carlo (MCMC) is a widely used method for sampling, many gaps remain in understanding its performance.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIn this talk, I will show tight analysis for Markov chains to sample from various discrete distributions using entropic and spectral independence, which are recently developed notions of discrete log-concavity. In particular l will show the optimal mixing time of the Glauber dynamics to sample weighted independent sets of graphs, also known as the hardcore model.\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003ETitle: Tight Markov chain analysis using discrete log-concavity\u003C\/p\u003E\r\n\r\n\u003Cp\u003EAbstract:\u003C\/p\u003E\r\n\r\n\u003Cp\u003ESampling is a fundamental task with many applications in algorithm design and in machine learning. Sampling from high-dimensional discrete distributions, such as Ising models, has long been studied for its applications in statistical physics, image modeling, and neural networks, as well as its connection to complexity theory. While Markov chain Monte Carlo (MCMC) is a widely used method for sampling, many gaps remain in understanding its performance.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIn this talk, I will show tight analysis for Markov chains to sample from various discrete distributions using entropic and spectral independence, which are recently developed notions of discrete log-concavity. In particular l will show the optimal mixing time of the Glauber dynamics to sample weighted independent sets of graphs, also known as the hardcore model.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Tight Markov chain analysis using discrete log-concavity"}],"uid":"36512","created_gmt":"2023-09-16 20:24:26","changed_gmt":"2023-09-16 20:24:26","author":"wperkins3","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-10-02T11:00:00-04:00","event_time_end":"2023-10-02T12:00:00-04:00","event_time_end_last":"2023-10-02T12:00:00-04:00","gmt_time_start":"2023-10-02 15:00:00","gmt_time_end":"2023-10-02 16:00:00","gmt_time_end_last":"2023-10-02 16:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Klaus 1116","extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"669706":{"#nid":"669706","#data":{"type":"event","title":"ARC Colloquium: Lijie Chen (Berkeley); Pettit 102 at 11am","body":[{"value":"\u003Cp\u003ELijie Chen (Berkeley)\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle: Polynomial -Time Pseudodeterministic Construction of Primes\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u0026nbsp;A randomized algorithm for a search problem is pseudodeterministic if it produces a fixed canonical solution to the search problem with high probability. In their seminal work on the topic, Gat and Goldwasser posed as their main open problem whether prime numbers can be pseudodeterministically constructed in polynomial time. We provide a positive solution to this question in the infinitely-often regime. In more detail, we give an unconditional polynomial-time randomized algorithm B such that, for infinitely many values of n, B(1^n) outputs a canonical n-bit prime p_n with high probability. More generally, we prove that for every dense property Q of strings that can be decided in polynomial time, there is an infinitely-often pseudodeterministic polynomial-time construction of strings satisfying Q. This improves upon a subexponential-time construction of Oliveira and Santhanam. Our construction uses several new ideas, including a novel bootstrapping technique for pseudodeterministic constructions, and a quantitative optimization of the uniform hardness-randomness framework of Chen and Tell, using a variant of the Shaltiel-Umans generator. This talk is based on joint work with Zhenjian Lu, Igor C. Oliveira, Hanlin Ren, and Rahul Santhanam.\u003C\/strong\u003E\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle: Polynomial -Time Pseudodeterministic Construction of Primes\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u0026nbsp;A randomized algorithm for a search problem is pseudodeterministic if it produces a fixed canonical solution to the search problem with high probability. In their seminal work on the topic, Gat and Goldwasser posed as their main open problem whether prime numbers can be pseudodeterministically constructed in polynomial time. We provide a positive solution to this question in the infinitely-often regime. In more detail, we give an unconditional polynomial-time randomized algorithm B such that, for infinitely many values of n, B(1^n) outputs a canonical n-bit prime p_n with high probability. More generally, we prove that for every dense property Q of strings that can be decided in polynomial time, there is an infinitely-often pseudodeterministic polynomial-time construction of strings satisfying Q. This improves upon a subexponential-time construction of Oliveira and Santhanam. Our construction uses several new ideas, including a novel bootstrapping technique for pseudodeterministic constructions, and a quantitative optimization of the uniform hardness-randomness framework of Chen and Tell, using a variant of the Shaltiel-Umans generator. This talk is based on joint work with Zhenjian Lu, Igor C. Oliveira, Hanlin Ren, and Rahul Santhanam.\u003C\/strong\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Polynomial -Time Pseudodeterministic Construction of Primes"}],"uid":"36512","created_gmt":"2023-09-16 20:21:09","changed_gmt":"2023-09-16 20:21:09","author":"wperkins3","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-09-25T11:00:00-04:00","event_time_end":"2023-09-25T12:00:00-04:00","event_time_end_last":"2023-09-25T12:00:00-04:00","gmt_time_start":"2023-09-25 15:00:00","gmt_time_end":"2023-09-25 16:00:00","gmt_time_end_last":"2023-09-25 16:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Pettit 102","extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"669705":{"#nid":"669705","#data":{"type":"event","title":"ARC Colloquium: ARC Fellowship Presentations (Klaus 1116, 11am)","body":[{"value":"\u003Cp\u003EAt 11am in Klaus 1116 we will have a special ARC colloquium featuring some of last spring\u0027s\u0026nbsp;\u003Ca href=\u0022https:\/\/arc.gatech.edu\/education\u0022 id=\u0022LPlnk158945\u0022 title=\u0022https:\/\/arc.gatech.edu\/education\u0022\u003EARC Student Fellowship\u003C\/a\u003E\u0026nbsp;awardees presenting on work they did while supported by the fellowships.\u0026nbsp; The schedule is below.\u0026nbsp; We will also give information on what an ARC fellowship is and how to apply for an ARC fellowship this year.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ESchedule\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EXinyuan Cao \u0022Unsupervised Halfspace Learning in Polynomial Time\u0022\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EYuzhou Wang \u0022On the hardness of finding balanced independent sets in random bipartite graphs\u0022\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EJai Moondra \u0022Existence and Approximations for Fair Solution Portfolios\u0022\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EYongchun Li \u0022On the Partial Convexification of the Low-rank Constrained Optimization\u0022\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EKevin Shu: \u0022Accelerated Gradient Descent Via Long Steps\u0022\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003ETian-Yi Zhu \u0022Classification of Data Generated by Gaussian Mixture Models Using Deep ReLU Networks\u0022\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EConclusion + lunch\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EA special ARC colloquium featuring some of last spring\u0027s\u0026nbsp;\u003Ca href=\u0022https:\/\/arc.gatech.edu\/education\u0022 id=\u0022LPlnk158945\u0022 title=\u0022https:\/\/arc.gatech.edu\/education\u0022\u003EARC Student Fellowship\u003C\/a\u003E\u0026nbsp;awardees presenting on work they did while supported by the fellowships.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"ARC Fellowship presentations"}],"uid":"36512","created_gmt":"2023-09-16 20:16:58","changed_gmt":"2023-09-16 20:16:58","author":"wperkins3","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-09-18T11:00:00-04:00","event_time_end":"2023-09-18T12:00:00-04:00","event_time_end_last":"2023-09-18T12:00:00-04:00","gmt_time_start":"2023-09-18 15:00:00","gmt_time_end":"2023-09-18 16:00:00","gmt_time_end_last":"2023-09-18 16:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Klaus 1116","extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"669532":{"#nid":"669532","#data":{"type":"event","title":"ARC Colloquium: Zongchen Chen (Buffalo), 11am Klaus 2447","body":[{"value":"\u003Cdiv\u003E\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cstrong\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/strong\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cdiv\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cstrong\u003EZongchen Chen\u003C\/strong\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/div\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cstrong\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003ESeptember 14, 2023\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/strong\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cstrong\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EKlaus 2447 \u2013 11:00 AM\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/strong\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u0026nbsp;\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003ETitle:\u0026nbsp;\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003Cbr \/\u003E\r\n\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003ESampling from Graphical Models via Spectral Independence\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\n\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EAbstract:\u0026nbsp;\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/div\u003E\r\n\r\n\u003Cdiv\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EIn many scientific settings we use a statistical model to describe a high-dimensional distribution over many variables. Such models are often\u0026nbsp;represented as a weighted graph encoding the dependencies between different variables and are known as graphical models. Graphical\u0026nbsp;models arise in a wide variety of scientific fields throughout science and engineering.\u0026nbsp;\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/div\u003E\r\n\r\n\u003Cdiv\u003E\u003Cbr \/\u003E\r\n\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EOne fundamental task for graphical models is to generate random samples from the associated distribution. The Markov chain Monte Carlo\u0026nbsp;(MCMC) method is one of the simplest and most popular approaches to tackle such problems. Despite the popularity of graphical models and\u0026nbsp;MCMC algorithms, theoretical guarantees of their performance are not known even for some simple models. I will describe a new tool called\u0026nbsp;\u0022spectral independence\u0022 to analyze MCMC algorithms and more importantly to reveal the underlying structure behind such models. I will also\u0026nbsp;discuss how these structural properties can be applied to sampling when MCMC fails and to other statistical problems like parameter learning\u0026nbsp;or model fitting.\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cdiv\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E---------------------------------------------------------------\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/div\u003E\r\n\r\n\u003Cdiv\u003E\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Ca href=\u0022https:\/\/sites.google.com\/view\/zongchenchen\/home\u0022 id=\u0022OWA0532010a-b1e2-c458-6cb0-aa9764c55809\u0022 rel=\u0022noopener noreferrer\u0022 target=\u0022_blank\u0022 title=\u0022https:\/\/sites.google.com\/view\/zongchenchen\/home\u0022\u003ESpeaker\u0027s Webpage\u003C\/a\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cdiv\u003E\u0026nbsp;\u003C\/div\u003E\r\n\r\n\u003Cdiv\u003E\u0026nbsp;\u003C\/div\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cem\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EVideos of recent talks are available at:\u0026nbsp;\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/em\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022 id=\u0022OWA70e53f23-eca3-372e-c638-9ed9a23e9263\u0022 rel=\u0022noopener noreferrer\u0022 target=\u0022_blank\u0022\u003E\u003Cem\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/em\u003E\u003C\/a\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003Cem\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u0026nbsp;and\u0026nbsp;\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/em\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Ca href=\u0022http:\/\/arc.gatech.edu\/node\/121\u0022 id=\u0022OWA7a01bce1-9025-58cd-b923-2e8c38bcc4a7\u0022 rel=\u0022noopener noreferrer\u0022 target=\u0022_blank\u0022\u003E\u003Cem\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003Ehttp:\/\/arc.gatech.edu\/node\/121\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/em\u003E\u003C\/a\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\u003C\/div\u003E\r\n\u003C\/div\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003ETitle:\u0026nbsp;\u003Cbr \/\u003E\r\nSampling from Graphical Models via Spectral Independence\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\nAbstract:\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIn many scientific settings we use a statistical model to describe a high-dimensional distribution over many variables. Such models are often\u0026nbsp;represented as a weighted graph encoding the dependencies between different variables and are known as graphical models. Graphical\u0026nbsp;models arise in a wide variety of scientific fields throughout science and engineering.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cbr \/\u003E\r\nOne fundamental task for graphical models is to generate random samples from the associated distribution. The Markov chain Monte Carlo\u0026nbsp;(MCMC) method is one of the simplest and most popular approaches to tackle such problems. Despite the popularity of graphical models and\u0026nbsp;MCMC algorithms, theoretical guarantees of their performance are not known even for some simple models. I will describe a new tool called\u0026nbsp;\u0022spectral independence\u0022 to analyze MCMC algorithms and more importantly to reveal the underlying structure behind such models. I will also\u0026nbsp;discuss how these structural properties can be applied to sampling when MCMC fails and to other statistical problems like parameter learning\u0026nbsp;or model fitting.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Sampling from Graphical Models via Spectral Independence"}],"uid":"36512","created_gmt":"2023-09-07 22:15:43","changed_gmt":"2023-09-07 22:15:43","author":"wperkins3","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-09-14T11:00:00-04:00","event_time_end":"2023-09-14T12:00:00-04:00","event_time_end_last":"2023-09-14T12:00:00-04:00","gmt_time_start":"2023-09-14 15:00:00","gmt_time_end":"2023-09-14 16:00:00","gmt_time_end_last":"2023-09-14 16:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Klaus 2447","extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"669412":{"#nid":"669412","#data":{"type":"event","title":"TetFest60: Probabilistic Trajectories in Algorithms and Combinatorics","body":[{"value":"\u003Cp\u003EThe occasion of the workshop is a reflection on the\u0026nbsp;\u003Ca href=\u0022https:\/\/math.gatech.edu\/news\/random-approx-2023-tetfest60\u0022 rel=\u0022noreferrer noopener\u0022 target=\u0022_blank\u0022\u003Eremarkable career\u003C\/a\u003E\u0026nbsp;of\u0026nbsp;\u003Ca href=\u0022https:\/\/tetali.github.io\/\u0022 rel=\u0022noreferrer noopener\u0022 target=\u0022_blank\u0022\u003EPrasad Tetali\u003C\/a\u003E, currently Head of Mathematical Sciences at Carnegie Mellon and formerly professor of Mathematics and Computer Science at Georgia Tech. The workshop will highlight this by focusing on the many research directions influenced by Tetali\u2019s career. Confirmed speakers include researchers in Algorithms, Combinatorics and Probability, with all speakers crossing these boundaries.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EFor more details see here:\u0026nbsp;https:\/\/sites.gatech.edu\/tetfest60\/\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EGeorgia Tech will host a 2-day workshop (September 9-10) on the rich interplay between randomness, algorithms, and discrete mathematics with a view towards both the history of how these topics came together and flourished and exciting future directions and challenges. The workshop will take place just before the RANDOM-APPROX conference\u0026nbsp;(September 11-13, hosted by Georgia Tech), and we expect many participants to attend both events.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EFor a full schedule see \u003Ca href=\u0022https:\/\/sites.gatech.edu\/tetfest60\/\u0022\u003Ehere\u003C\/a\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"A workshop on probability, algorithms, and combinatorics"}],"uid":"36512","created_gmt":"2023-09-04 22:02:13","changed_gmt":"2023-09-05 11:36:10","author":"wperkins3","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-09-09T00:00:00-04:00","event_time_end":"2023-09-10T23:59:59-04:00","event_time_end_last":"2023-09-10T23:59:59-04:00","gmt_time_start":"2023-09-09 04:00:00","gmt_time_end":"2023-09-11 03:59:59","gmt_time_end_last":"2023-09-11 03:59:59","rrule":null,"timezone":"America\/New_York"},"location":"Klaus 1116","extras":[],"related_links":[{"url":"https:\/\/sites.gatech.edu\/tetfest60\/","title":"TetFest60"}],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1789","name":"Conference\/Symposium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"669413":{"#nid":"669413","#data":{"type":"event","title":"RANDOM-APPROX 2023","body":[{"value":"\u003Cp\u003EPlease see \u003Ca href=\u0022https:\/\/sites.gatech.edu\/randomapprox2023\/\u0022\u003Ehere\u003C\/a\u003E for further information and registration.\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EGeorgia Tech hosts the RANDOM and APPROX conferences in 2023.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Georgia Tech will host the yearly computer science conferences "}],"uid":"36512","created_gmt":"2023-09-04 22:05:29","changed_gmt":"2023-09-04 22:05:29","author":"wperkins3","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-09-11T00:00:00-04:00","event_time_end":"2023-09-13T23:59:59-04:00","event_time_end_last":"2023-09-13T23:59:59-04:00","gmt_time_start":"2023-09-11 04:00:00","gmt_time_end":"2023-09-14 03:59:59","gmt_time_end_last":"2023-09-14 03:59:59","rrule":null,"timezone":"America\/New_York"},"location":"Bill Moore Student Success Center","extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1789","name":"Conference\/Symposium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"669411":{"#nid":"669411","#data":{"type":"event","title":"ARC Colloquium: Mark Jerrum (Queen Mary)","body":[{"value":"\u003Cp\u003EARC Colloquium 9\/5\/2023 11am in Petit 102A\u003C\/p\u003E\r\n\r\n\u003Cp\u003EMark Jerrum (Queen Mary)\u003C\/p\u003E\r\n\r\n\u003Cp\u003ETitle: Counting vertices of integral polytopes defined by facets\u003C\/p\u003E\r\n\r\n\u003Cp\u003EAbstract:\u0026nbsp; I\u0027ll address the computational complexity of counting vertices of an integral polytope defined by a system of linear inequalities.\u0026nbsp; The focus will be on polytopes with small integer vertices, particularly 0\/1 and half-integral polytopes.\u0026nbsp; The geometric approach to combinatorial optimisation, as explored in Schrijver\u0027s 3-volume monograph, provides plentiful examples of these.\u0026nbsp; The complexity of exact counting is pretty well understood, so I\u0027ll concentrate on approximate counting with guaranteed error bounds.\u0026nbsp; The complexity landscape is only partially understood, but there appear to be natural examples that are neither in P nor NP-hard.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThis is joint work with Heng Guo (Edinburgh)\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EARC Colloquium\u0026nbsp; 9\/5\/2023\u003C\/p\u003E\r\n\r\n\u003Cp\u003E11am, Petit 102\u003C\/p\u003E\r\n\r\n\u003Cp\u003EMark Jerrum (Queen Mary)\u003Cbr \/\u003E\r\n\u0026nbsp;\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Counting vertices of integral polytopes defined by facets"}],"uid":"36512","created_gmt":"2023-09-04 21:20:29","changed_gmt":"2023-09-04 21:30:55","author":"wperkins3","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-09-05T11:00:00-04:00","event_time_end":"2023-09-05T12:00:00-04:00","event_time_end_last":"2023-09-05T12:00:00-04:00","gmt_time_start":"2023-09-05 15:00:00","gmt_time_end":"2023-09-05 16:00:00","gmt_time_end_last":"2023-09-05 16:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Petit 102A","extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"667220":{"#nid":"667220","#data":{"type":"event","title":"ACO Alumni Lecture featuring Daniel Dadush (Centrum Wiskunde and Informatica)","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EDaniel Dadush (Centrum Wiskunde and Informatica)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EApril 17, 2023\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EKlaus 1116 - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp;\u003C\/strong\u003EInterior point methods are not worse than Simplex\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003E\u003Cspan\u003EWhereas interior point methods provide polynomial-time linear programming algorithms, the running time bounds depend on bit-complexity or condition measures that can be unbounded in the problem dimension. This is in contrast with the classical simplex method that always admits an exponential bound. We introduce a new polynomial-time path-following interior point method where the number of iterations also admits a combinatorial upper bound O(2^n n^{1.5} log n) for an n-variable linear program in standard form. This complements previous work by Allamigeon, Benchimol, Gaubert, and Joswig (SIAGA 2018) that exhibited a family of instances where any path-following method must take exponentially many iterations. The number of iterations of our algorithm is at most O(n^{1.5} log n) times the number of segments of any piecewise linear curve in the wide neighborhood of the central path. In particular, it matches the number of iterations of any path following interior point method up to this polynomial factor. The overall exponential upper bound derives from studying the \u2018max central path\u2019, a piecewise-linear curve with the number of pieces bounded by the total length of n shadow vertex simplex paths. This is joint work with Xavier Allamigeon (INRIA \/ Ecole Polytechnique), Georg Loho (U. Twente), Bento Natura (LSE), Laszlo Vegh (LSE).\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E---------------------------------------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/homepages.cwi.nl\/~dadush\/\u0022\u003ESpeaker\u0027s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003Cem\u003E and \u003Ca href=\u0022http:\/\/arc.gatech.edu\/node\/121\u0022\u003Ehttp:\/\/arc.gatech.edu\/node\/121\u003C\/a\u003E \u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003EAbstract : \u003C\/span\u003E\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EInterior point methods are not worse than Simplex\u0026nbsp;\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Title : Interior point methods are not worse than Simplex  Klaus 1116 at 11am"}],"uid":"34983","created_gmt":"2023-04-11 01:36:26","changed_gmt":"2023-04-11 01:36:26","author":"Mohit Singh","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-04-17T11:00:00-04:00","event_time_end":"2023-04-17T12:00:00-04:00","event_time_end_last":"2023-04-17T12:00:00-04:00","gmt_time_start":"2023-04-17 15:00:00","gmt_time_end":"2023-04-17 16:00:00","gmt_time_end_last":"2023-04-17 16:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Klaus 1116","extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"663664":{"#nid":"663664","#data":{"type":"event","title":"ARC Colloquium: Viswanath Nagarajan (University of Michigan) ","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EViswanath Nagarajan (University of Michigan)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EApril 3, 2023\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EKlaus 1116 - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle\u003C\/strong\u003E: Stochastic Score Classification and Halfspace Intersection\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\n\u003Cstrong\u003EAbstract\u003C\/strong\u003E: In sequential testing, we have a complex system with several components, each of which is \u0022working\u0022 or \u0022failed\u0022 with some independent probability. We are interested in evaluating the system status, which is a function of the statuses of its components. The goal is to design a policy that minimizes the expected cost of testing. Prior work has mainly focused on simple functions like k-of-n and halfspaces. We consider more general \u0022score classification\u0022 functions, and provide the first constant-factor approximation algorithm. Our result improves over a previous logarithmic approximation ratio. Moreover, our policy is non adaptive: it just involves performing tests in an a-priori fixed order. Finally, in computational experiments on random instances, we observe that the cost of our algorithm is typically within 50% of an information-theoretic lower bound.\u0026nbsp;\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E---\u003C\/p\u003E\r\n\r\n\u003Cp\u003E---------------------------------------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/viswa.engin.umich.edu\/\u0022\u003ESpeaker\u0027s Webpage\u003C\/a\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003Cem\u003E and \u003Ca href=\u0022http:\/\/arc.gatech.edu\/node\/121\u0022\u003Ehttp:\/\/arc.gatech.edu\/node\/121\u003C\/a\u003E \u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003ETitle: Stochastic Score Classification and Halfspace Intersection\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Title: Stochastic Score Classification and Halfspace Intersection: Klaus 1116 at 11:00 AM"}],"uid":"35702","created_gmt":"2022-12-06 18:23:02","changed_gmt":"2023-03-31 15:45:29","author":"mb121","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-04-03T11:00:00-04:00","event_time_end":"2023-04-03T12:00:00-04:00","event_time_end_last":"2023-04-03T12:00:00-04:00","gmt_time_start":"2023-04-03 15:00:00","gmt_time_end":"2023-04-03 16:00:00","gmt_time_end_last":"2023-04-03 16:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Klaus 1116","extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"663676":{"#nid":"663676","#data":{"type":"event","title":"ARC Colloquium: Guy Bresler (MIT) ","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EGuy Bresler (MIT)\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EMarch 13, 2023\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EKlaus 1116 - 11:00 am\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Ch3\u003E\u0026nbsp;\u003C\/h3\u003E\r\n\r\n\u003Ch3\u003E\u0026nbsp;\u003C\/h3\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003ETitle:\u0026nbsp;Algorithmic Decorrelation and Planted Clique in Dependent Random Graphs\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EAbstract: There is a growing collection of average-case reductions starting from Planted Clique (or Planted Dense Subgraph) and mapping to a variety of statistics problems, sharply characterizing their computational phase transitions. These reductions transform an instance of Planted Clique, a highly structured problem with its simple clique signal and independent noise, to problems with richer structure. In this talk we aim to make progress in the other direction: to what extent can these problems, which often have complicated dependent noise, be transformed back to Planted Clique? Such a bidirectional reduction between Planted Clique and another problem shows a strong computational equivalence between the two problems. As a concrete instance of a more general result, we consider the planted clique (or dense subgraph) problem in an ambient graph that has dependent edges induced by randomly adding triangles to the Erdos-Renyi graph G(n,p), and show how to successfully eliminate dependence by carefully removing the triangles while approximately preserving the clique (or dense subgraph). In order to analyze our reduction we develop new methods for bounding the total variation distance between dependent distributions.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EBio\u003C\/strong\u003E:\u0026nbsp;Guy\u0026nbsp;Bresler\u0026nbsp;is an associate professor in the Department of Electrical Engineering and Computer Science at MIT, and a member of LIDS and IDSS. A major focus of his research is on the computational complexity of statistical inference, a direction that combines his interests in information theory, probability, and computation. \u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/www.mit.edu\/~gbresler\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003Cem\u003E and \u003Ca href=\u0022http:\/\/arc.gatech.edu\/node\/121\u0022\u003Ehttp:\/\/arc.gatech.edu\/node\/121\u003C\/a\u003E \u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Title    Title: Algorithmic Decorrelation and Planted Clique in Dependent Random Graphs: Klaus 1116 at 11:00 AM"}],"uid":"35702","created_gmt":"2022-12-06 23:33:28","changed_gmt":"2023-03-06 23:17:13","author":"mb121","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-03-13T12:00:00-04:00","event_time_end":"2023-03-13T13:00:00-04:00","event_time_end_last":"2023-03-13T13:00:00-04:00","gmt_time_start":"2023-03-13 16:00:00","gmt_time_end":"2023-03-13 17:00:00","gmt_time_end_last":"2023-03-13 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"665602":{"#nid":"665602","#data":{"type":"event","title":"ACO Student Seminar:  Gregory Kehne (Harvard)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms, Combinatorics \u0026amp; Optimization\u0026nbsp;(ACO)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EGregory Kehne (Harvard)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EFebruary 24, 2023\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003ESkiles 005 - 1:00 pm\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E Online Covering: Prophets, Secretaries,\u0026nbsp;and Samples\u003Cstrong\u003E \u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp;\u0026nbsp;\u003C\/strong\u003EWe give a polynomial-time algorithm for online covering IPs with a competitive ratio of O(\\log mn) when the constraints are revealed in random order, essentially matching the best possible offline bound of \\Omega(\\log n) and circumventing the \\Omega(\\log m \\log n) lower bound known in adversarial order. We then leverage this O(\\log mn)-competitive algorithm to solve this problem in the prophet setting, where constraints are sampled from a sequence of known distributions. Our reduction in fact relies only on samples from these distributions, in a manner evocative of prior work on single-sample prophet inequalities for online packing problems. We present sample guarantees in the prophet setting, as well as in the setting where random samples from an adversarial instance are revealed at the outset.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThis talk is based on joint work with Anupam Gupta and Roie Levin, part of which appeared at FOCS 2021.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E---------------------------------------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/gregorykehne.com\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003Cem\u003E and \u003Ca href=\u0022http:\/\/arc.gatech.edu\/node\/121\u0022\u003Ehttp:\/\/arc.gatech.edu\/node\/121\u003C\/a\u003E \u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Online Covering: Prophets, Secretaries, and Samples - Skiles 005 at 1:00 PM"}],"uid":"35702","created_gmt":"2023-02-08 18:28:35","changed_gmt":"2023-02-16 20:49:03","author":"mb121","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-02-24T13:00:00-05:00","event_time_end":"2023-02-24T14:00:00-05:00","event_time_end_last":"2023-02-24T14:00:00-05:00","gmt_time_start":"2023-02-24 18:00:00","gmt_time_end":"2023-02-24 19:00:00","gmt_time_end_last":"2023-02-24 19:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"665072":{"#nid":"665072","#data":{"type":"event","title":"ARC Colloquium: Rohan Ghuge (University of Michigan)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003ERohan Ghuge (University of Michigan)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EFebruary 13, 2023\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022Center\u0022\u003E\u003Cstrong\u003EPettit Microelectronics Building, Room 102 A\u0026amp;B - 2:00 pm\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E The Power of Adaptivity for Decision-Making under Uncertainty\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003EIn this talk, we discuss the role of adaptivity in decision-making problems under uncertainty. The first part of the talk focuses on stochastic combinatorial optimization problems, while the second part deals with the K-armed dueling bandits problem.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003ECombinatorial optimization captures many natural decision-making\u0026nbsp;problems such as matching, assortment optimization,\u0026nbsp;and submodular optimization. In many practical settings, we have to solve such combinatorial problems under uncertainty; specifically when we\u0026nbsp;only have partial knowledge about the input. Solutions to such\u0026nbsp;problems are sequential decision processes that make decisions one\u0026nbsp;by one \u0026ldquo;adaptively\u0026rdquo; (depending on prior observations). While such\u0026nbsp;adaptive solutions achieve the best objective, the inherently\u0026nbsp;sequential nature makes them undesirable in many applications. Specifically, we ask: \u003Cem\u003Ehow well can solutions with few adaptive rounds approximate fully-adaptive solutions? \u003C\/em\u003EWe study (and answer) this question for the stochastic submodular cover problem, where one needs to select a subset of stochastic items to cover a submodular function at minimum expected cost. This model captures many problems such as sensor placement with unreliable sensors, optimal decision tree, stochastic set cover, and correlated knapsack cover. We show how to obtain solutions that approximate fully-adaptive solutions using only a few \u0026ldquo;rounds\u0026rdquo; of adaptivity for the stochastic submodular cover problem. We study both independent and correlated settings, proving \u003Cem\u003Esmooth tradeoffs between the number of adaptive rounds and the solution quality\u003C\/em\u003E. We also present experimental results demonstrating that a few rounds of adaptivity suffice to obtain high-quality solutions in practice.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIn the second part of the talk, we discuss the K-armed dueling bandits problem, a variation of the multi-armed bandit problem where the feedback is in the form of noisy pairwise comparisons. This problem has applications in a wide-variety of domains like search ranking, recommendation systems and sports ranking where eliciting qualitative feedback is easy while real-valued feedback is not easily interpretable; thus, it has been a popular topic of research in the machine learning community. Previous works have only focused on the sequential setting where the learning policy adapts after every comparison. However, in many applications such as search ranking and recommendation systems, it is preferable to perform comparisons in a limited number of parallel batches. We \u003Cem\u003Eintroduce and study the batched dueling bandits problem\u003C\/em\u003E, for which we design algorithms with a \u003Cem\u003Esmooth trade-off between the number of batches and regret\u003C\/em\u003E. Our regret bounds match the best known sequential regret bounds (up to poly-logarithmic factors), using only a logarithmic number (in the time horizon) of batches.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E---------------------------------------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022http:\/\/rohanghuge.com\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003Cem\u003E and \u003Ca href=\u0022http:\/\/arc.gatech.edu\/node\/121\u0022\u003Ehttp:\/\/arc.gatech.edu\/node\/121\u003C\/a\u003E \u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"The Power of Adaptivity for Decision-Making under Uncertainty - Pettit 102 A\u0026B at 2:00 PM"}],"uid":"35702","created_gmt":"2023-01-25 12:41:38","changed_gmt":"2023-02-07 13:04:23","author":"mb121","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-02-13T14:00:00-05:00","event_time_end":"2023-02-13T15:00:00-05:00","event_time_end_last":"2023-02-13T15:00:00-05:00","gmt_time_start":"2023-02-13 19:00:00","gmt_time_end":"2023-02-13 20:00:00","gmt_time_end_last":"2023-02-13 20:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"664894":{"#nid":"664894","#data":{"type":"event","title":"ARC Colloquium: Dylan Altschuler (NYU)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EDylan Altschuler\u0026nbsp;(NYU)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EJanuary 30, 2023\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E The critical window of the symmetric perceptron\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003EWe study a random constraint satisfaction problem called the\u003Cem\u003E symmetric binary perceptron\u003C\/em\u003E (SBP). The SBP is closely related to long-standing conjectures in combinatorics and statistical physics. Our goal is to characterize the \u0026ldquo;critical window\u0026rdquo; of the SBP. Namely, how many constraints do we need to add for the probability of satisfiability to drop from .99 to .01?\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EOur main result is that the satisfiability transition of the SBP corresponds to the addition of a nearly constant number of clauses. This adds the SBP to a short list of random satisfaction problems for which the critical window is rigorously known to be this small. Interestingly, the critical window of the SBP is far smaller than standard techniques would suggest, a phenomenon known as \u0026ldquo;superconcentration\u0026rdquo;.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/arxiv.org\/abs\/2205.02319\u0022 target=\u0022_blank\u0022\u003Ehttps:\/\/arxiv.org\/abs\/2205.02319\u003C\/a\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E---------------------------------------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/dylanaltschuler.github.io\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003Cem\u003E and \u003Ca href=\u0022http:\/\/arc.gatech.edu\/node\/121\u0022\u003Ehttp:\/\/arc.gatech.edu\/node\/121\u003C\/a\u003E \u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"The critical window of the symmetric perceptron - Klaus 1116 at 11:00 AM"}],"uid":"35702","created_gmt":"2023-01-19 13:36:37","changed_gmt":"2023-01-23 18:30:48","author":"mb121","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-01-30T11:00:00-05:00","event_time_end":"2023-01-30T12:00:00-05:00","event_time_end_last":"2023-01-30T12:00:00-05:00","gmt_time_start":"2023-01-30 16:00:00","gmt_time_end":"2023-01-30 17:00:00","gmt_time_end_last":"2023-01-30 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"664681":{"#nid":"664681","#data":{"type":"event","title":"ARC\/Neuroscience Joint Seminar:  Christos Papadimitriou, Columbia University","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EARC\/Neuroscience Joint Seminar\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EChristos Papadimitriou (Columbia University)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, January 23, 2023, 11:15\u0026nbsp;am \u0026ndash; 12:15\u0026nbsp;pm\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EEBB, Room 1005\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003ETo participate virtually,\u0026nbsp;\u003Cstrong\u003E\u003Cem\u003E\u003Ca href=\u0022https:\/\/gatech.zoom.us\/j\/96163544579\u0022\u003ECLICK HERE\u003C\/a\u003E\u003C\/em\u003E\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E Towards Biologically Plausible Intelligence\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp;\u0026nbsp;\u003C\/strong\u003EThere is no doubt that cognition and intelligence are the results of neural activity - but how, exactly? How do molecules, neurons, and synapses give rise to reasoning, language, plans, stories, art, math? Despite dazzling progress in experimental neuroscience, as well as in cognitive science, we do not seem to be making progress on the overarching question. As Richard Axel recently put it in an interview: \u0026quot;We don\u0026#39;t have a logic for the transformation of neuronal activity to thought and action. I view discerning [this] logic as the most important future direction of neuroscience\u0026quot;. What kind of formal system would qualify as this \u0026quot;logic\u0026quot;? I will introduce a mathematical model of the brain, which arguably captures the basic tenets of neuroscience and can be simulated efficiently; its main emergent behavior are assemblies of neurons, representations of stimuli, concepts, words, etc. \u0026nbsp;Using this framework a Parser was constructed which (a) can handle reasonably complex sentences in English and other languages; and (b) works exclusively through the firing of biologically realistic neurons. \u0026nbsp;I will discuss ongoing work aiming to reproduce language acquisition in a biologically plausible way.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E\u0026nbsp;\u0026nbsp;Christos Harilaos Papadimitriou is the Donovan Family Professor of Computer Science at Columbia University. Before joining Columbia in 2017, he was a professor at UC Berkeley for the previous 22 years, and before that he taught at Harvard, MIT, NTU Athens, Stanford, and UCSD. He has written five textbooks and many articles on algorithms and complexity, and their applications to optimization, databases, control, AI, robotics, economics and game theory, the Internet, evolution, and the brain. He holds a PhD from Princeton (1976), and eight honorary doctorates, including from ETH, University of Athens, EPFL, and Univ. de Paris Dauphine. He is a member of the National Academy of Sciences of the US, the American Academy of Arts and Sciences, and the National Academy of Engineering, and he has received the Knuth prize, the Go\u0026quot;del prize, the Babbage award, the von Neumann medal, as well as the 2018 Harvey Prize by Technion. In 2015 the president of the Hellenic republic named him commander of the order of the Phoenix. He has also written three novels: \u0026quot;Turing,\u0026quot; \u0026quot;Logicomix\u0026quot; and his latest \u0026quot;Independence.\u0026quot;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003ENote: Lunch provided for in-person attendees.\u0026nbsp;\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/neuro.gatech.edu\/seminar-series\/2022-2023\u0022\u003E2022-2023 GT Neuro Seminar Series - Mondays at 11:15 AM\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E---------------------------------------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EFor an archive of all GT Neuro Seminar recordings, including abstracts, talk transcripts, and videos, please visit this link:\u0026nbsp;\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/55889\u0022\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/55889\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u003Ca href=\u0022https:\/\/neuro.gatech.edu\/georgia-tech-neuro-seminar-series-10\u0022\u003Ehttps:\/\/neuro.gatech.edu\/georgia-tech-neuro-seminar-series-10\u003C\/a\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Towards Biologically Plausible Intelligence"}],"uid":"35702","created_gmt":"2023-01-12 15:05:17","changed_gmt":"2023-01-13 16:45:27","author":"mb121","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-01-23T11:15:00-05:00","event_time_end":"2023-01-23T12:15:00-05:00","event_time_end_last":"2023-01-23T12:15:00-05:00","gmt_time_start":"2023-01-23 16:15:00","gmt_time_end":"2023-01-23 17:15:00","gmt_time_end_last":"2023-01-23 17:15:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"related_links":[{"url":"https:\/\/neuro.gatech.edu\/georgia-tech-neuro-seminar-series-10","title":"\u0022Towards Biologically Plausible Intelligence\u0022"}],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Cstrong\u003EContact:\u003C\/strong\u003E\u0026nbsp;\u0026nbsp;\u003Ca href=\u0022mailto:connect@ibb.gatech.edu\u0022\u003Econnect@ibb.gatech.edu\u003C\/a\u003E\u0026nbsp;- event inquiries\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"661207":{"#nid":"661207","#data":{"type":"event","title":"ARC Colloquium: Elizabeth Yang (Berkeley)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EElizabeth Yang (Berkeley)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EJanuary 23, 2023\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EPettit Microelectronics Building 102 A\u0026amp;B - 3:30 pm\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E Testing thresholds for high-dimensional random geometric graphs\u003Cstrong\u003E \u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp;\u0026nbsp;\u003C\/strong\u003EIn the random geometric graph model, we identify each of our n vertices with an independently and uniformly sampled vector from the d-dimensional unit sphere, and we connect pairs of vertices whose vectors are \u0026quot;sufficiently close,\u0026quot; such that the marginal probability of each edge is p.\u0026nbsp;We investigate the problem of distinguishing an Erd\u0151s-R\u0026eacute;nyi graph from a random geometric graph.\u0026nbsp;When p = c \/ n for constant c, we prove that if d \u0026ge; poly log n, the total variation distance between the two distributions is close to 0; this improves upon the best previous bound of Brennan, Bresler, and Nagaraj (2020), which required d \u0026gt;\u0026gt; n^{3\/2}. Furthermore, our result is nearly tight, resolving a conjecture of Bubeck, Ding, Eldan, \u0026amp; R\u0026aacute;cz (2016) up to logarithmic factors.\u0026nbsp;We also obtain improved upper bounds on the statistical indistinguishability thresholds in d for the full range of p satisfying 1\/n \u0026le; p \u0026le; 1\/2, improving upon the previous bounds by polynomial factors.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIn this talk, we will discuss the key ideas in our proof, which include:\u003Cbr \/\u003E\r\n- Sharp estimates for the area of the intersection of a random sphere cap with an arbitrary subset of the sphere, which are obtained using optimal transport maps and entropy-transport inequalities on the unit sphere.\u003Cbr \/\u003E\r\n- Analyzing the Belief Propagation algorithm to characterize the distributions of (subsets of) the random vectors conditioned on producing a particular graph.\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\nBased on joint work with Siqi Liu, Sidhanth Mohanty, and Tselil Schramm.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E---------------------------------------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/people.eecs.berkeley.edu\/~elizabeth_yang\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003Cem\u003E and \u003Ca href=\u0022http:\/\/arc.gatech.edu\/node\/121\u0022\u003Ehttp:\/\/arc.gatech.edu\/node\/121\u003C\/a\u003E \u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Testing thresholds for high-dimensional random geometric graphs - Pettit Microelectronics Building 102 A\u0026B at 3:30pm"}],"uid":"35702","created_gmt":"2022-09-15 14:49:25","changed_gmt":"2023-01-12 20:48:26","author":"mb121","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-01-23T15:30:00-05:00","event_time_end":"2023-01-23T16:30:00-05:00","event_time_end_last":"2023-01-23T16:30:00-05:00","gmt_time_start":"2023-01-23 20:30:00","gmt_time_end":"2023-01-23 21:30:00","gmt_time_end_last":"2023-01-23 21:30:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"663663":{"#nid":"663663","#data":{"type":"event","title":"ARC Colloquium: Thodoris Lykouris (MIT) ","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EThodoris Lykouris (MIT)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMarch 27, 2023\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E TBA\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003ETBA\u003C\/p\u003E\r\n\r\n\u003Cp\u003E---------------------------------------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mitsloan.mit.edu\/faculty\/directory\/thodoris-lykouris\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003Cem\u003E and \u003Ca href=\u0022http:\/\/arc.gatech.edu\/node\/121\u0022\u003Ehttp:\/\/arc.gatech.edu\/node\/121\u003C\/a\u003E \u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Title TBA: Klaus 1116 at 11:00 AM"}],"uid":"35702","created_gmt":"2022-12-06 18:19:04","changed_gmt":"2022-12-06 18:19:04","author":"mb121","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-03-27T12:00:00-04:00","event_time_end":"2023-03-27T13:00:00-04:00","event_time_end_last":"2023-03-27T13:00:00-04:00","gmt_time_start":"2023-03-27 16:00:00","gmt_time_end":"2023-03-27 17:00:00","gmt_time_end_last":"2023-03-27 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"661214":{"#nid":"661214","#data":{"type":"event","title":"ARC Colloquium: Brice Huang (MIT)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EBrice Huang (MIT)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EDecember 5, 2022\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E Algorithmic Thresholds for Multi-Species Spin Glasses\u003Cstrong\u003E \u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003EThis talk focuses on optimizing the random and non-convex Hamiltonians of spherical spin glasses with multiple species. Our main result identifies the best possible value ALG achievable by class of Lipschitz algorithms and gives a matching algorithm in this class based on approximate message passing. The threshold ALG is given by a certain variational problem, which surprisingly may possess multiple optimizers.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EOur hardness result is proved using the Branching OGP introduced in our previous work [H-Sellke 21] to identify ALG for single-species spin glasses. This and all other OGPs for spin glasses have been proved using Guerra\u0026#39;s interpolation method. We introduce a new method to prove the Branching OGP which is both simpler and more robust. It works even for models in which the true maximum value of the objective function remains unknown.\u003Cbr \/\u003E\r\nBased on joint work with Mark Sellke.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E---------------------------------------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022http:\/\/www.bricehuang.com\/index.html\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003Cem\u003E and \u003Ca href=\u0022http:\/\/arc.gatech.edu\/node\/121\u0022\u003Ehttp:\/\/arc.gatech.edu\/node\/121\u003C\/a\u003E \u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Algorithmic Thresholds for Multi-Species Spin Glasses - Klaus 1116 at 11am"}],"uid":"35702","created_gmt":"2022-09-15 19:27:25","changed_gmt":"2022-11-18 20:57:00","author":"mb121","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-12-05T11:00:00-05:00","event_time_end":"2022-12-05T12:00:00-05:00","event_time_end_last":"2022-12-05T12:00:00-05:00","gmt_time_start":"2022-12-05 16:00:00","gmt_time_end":"2022-12-05 17:00:00","gmt_time_end_last":"2022-12-05 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"662483":{"#nid":"662483","#data":{"type":"event","title":"AI4OPT\/ARC Joint Seminar: Dylan Foster, Microsoft Research","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAI4OPT\/ARC Joint Seminar\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EDylan Foster (Microsoft Research)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EThursday, October 27, 2022, Noon \u0026ndash; 1:00 pm\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAtrium in Coda on the 9\u003Csup\u003Eth\u003C\/sup\u003E floor\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003EAlso live streamed at: \u003Ca href=\u0022https:\/\/gatech.zoom.us\/j\/99381428980\u0022\u003Ehttps:\/\/gatech.zoom.us\/j\/99381428980\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E The Statistical Complexity of Interactive Decision Making\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp;\u0026nbsp;\u003C\/strong\u003EA fundamental challenge in interactive learning and decision making, ranging from bandit problems to reinforcement learning, is to provide sample-efficient, adaptive learning algorithms that achieve near-optimal regret. This question is analogous to the classical problem of optimal (supervised) statistical learning, where there are well-known complexity measures (e.g., VC dimension and Rademacher complexity) that govern the statistical complexity of learning. However, characterizing the statistical complexity of interactive learning is substantially more challenging due to the adaptive nature of the problem. In this talk, we will introduce a new complexity measure, the Decision-Estimation Coefficient, which is necessary and sufficient for sample-efficient interactive learning. In particular, we will provide:\u003C\/p\u003E\r\n\r\n\u003Col\u003E\r\n\t\u003Cli\u003Ea lower bound on the optimal regret for any interactive decision making problem, establishing the Decision-Estimation Coefficient as a fundamental limit.\u003C\/li\u003E\r\n\t\u003Cli\u003Ea unified algorithm design principle, Estimation-to-Decisions, which attains a regret bound matching our lower bound, thereby achieving optimal sample-efficient learning as characterized by the Decision-Estimation Coefficient.\u003C\/li\u003E\r\n\u003C\/ol\u003E\r\n\r\n\u003Cp\u003ETaken together, these results give a theory of learnability for interactive decision making. When applied to reinforcement learning settings, the Decision-Estimation Coefficient recovers essentially all existing hardness results and lower bounds.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003ENote: Catered lunch will be served at the seminar. So, please stop by 15 minutes before the seminar to pick up lunch.\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E---------------------------------------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EClick here to sign up for AI4OPT seminar announcements:\u0026nbsp;\u0026nbsp;\u003Ca href=\u0022https:\/\/lists.isye.gatech.edu\/mailman\/listinfo\/ai4opt-seminars\u0022\u003Ehttps:\/\/lists.isye.gatech.edu\/mailman\/listinfo\/ai4opt-seminars\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"The Statistical Complexity of Interactive Decision Making"}],"uid":"35702","created_gmt":"2022-10-24 14:13:27","changed_gmt":"2022-10-24 14:13:27","author":"mb121","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-10-27T13:00:00-04:00","event_time_end":"2022-10-27T14:00:00-04:00","event_time_end_last":"2022-10-27T14:00:00-04:00","gmt_time_start":"2022-10-27 17:00:00","gmt_time_end":"2022-10-27 18:00:00","gmt_time_end_last":"2022-10-27 18:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"660906":{"#nid":"660906","#data":{"type":"event","title":"ARC Colloquium: David Wajc (Stanford) ","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EDavid Wajc (Stanford)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EOctober 24, 2022\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E TBA\u003Cstrong\u003E \u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003ETBA\u003C\/p\u003E\r\n\r\n\u003Cp\u003E---------------------------------------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/web.stanford.edu\/~wajc\/\u0022\u003ESpeaker\u0026rsquo;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003Cem\u003E and \u003Ca href=\u0022http:\/\/arc.gatech.edu\/node\/121\u0022\u003Ehttp:\/\/arc.gatech.edu\/node\/121\u003C\/a\u003E \u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Title TBA: Klaus 1116 at 11am"}],"uid":"35702","created_gmt":"2022-09-06 18:15:27","changed_gmt":"2022-09-06 18:15:27","author":"mb121","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-10-24T12:00:00-04:00","event_time_end":"2022-10-24T13:00:00-04:00","event_time_end_last":"2022-10-24T13:00:00-04:00","gmt_time_start":"2022-10-24 16:00:00","gmt_time_end":"2022-10-24 17:00:00","gmt_time_end_last":"2022-10-24 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"660244":{"#nid":"660244","#data":{"type":"event","title":"ARC Colloquium: Sanjeev Khanna (University of Pennsylvania)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003ESanjeev Khanna (University of Pennsylvania)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003ESeptember 19, 2022\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E On Regularity Lemma and Barriers in Streaming and Dynamic Matching\u003Cstrong\u003E \u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp;\u0026nbsp;\u003C\/strong\u003EWe present a new approach for finding matchings in dense graphs by building on Szemeredi\u0026#39;s celebrated Regularity Lemma. This allows us to obtain non-trivial albeit (very) slight improvements over long standing bounds for matchings in streaming and dynamic graphs. In particular, we establish the following results for $n$-vertex graphs:\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E(a) A single-pass streaming algorithm that finds a near-optimal matching in $o(n^2)$ bits of space. This constitutes the first single-pass, sublinear-space algorithm that improves over the trivial $1\/2$-approximation of the greedy algorithm.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E(b) A fully dynamic algorithm that with high probability maintains a near-optimal matching in $o(n)$ worst-case update time per edge update, improving upon the previous best update time. The algorithm works even against an adaptive adversary.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThe key idea behind both these results is to maintain a matching cover which is a \u0026ldquo;sparse\u0026rdquo; subgraph that approximately preserves matchings in each induced subgraph of the input graph. However, given the use of regularity lemma, the improvement obtained by our algorithms over trivial bounds is only by some function of $(log* n)$. Nevertheless, these results show that the \u0026ldquo;right\u0026rdquo; answer to these problems is not what is dictated by the previous bounds.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThis is joint work with Sepehr Assadi, Soheil Behnezhad, and Huan Li.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E---------------------------------------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/www.cis.upenn.edu\/~sanjeev\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003Cem\u003E and \u003Ca href=\u0022http:\/\/arc.gatech.edu\/node\/121\u0022\u003Ehttp:\/\/arc.gatech.edu\/node\/121\u003C\/a\u003E \u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"On Regularity Lemma and Barriers in Streaming and Dynamic Matching -  Klaus 1116 at 11am"}],"uid":"35702","created_gmt":"2022-08-17 13:55:15","changed_gmt":"2022-09-06 17:29:41","author":"mb121","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-09-19T12:00:00-04:00","event_time_end":"2022-09-19T13:00:00-04:00","event_time_end_last":"2022-09-19T13:00:00-04:00","gmt_time_start":"2022-09-19 16:00:00","gmt_time_end":"2022-09-19 17:00:00","gmt_time_end_last":"2022-09-19 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"660796":{"#nid":"660796","#data":{"type":"event","title":"ARC-ACO Lecture Series:  featuring Robert E. Tarjan (Princeton)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EARC - ACO Lecture Series\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cem\u003Efeaturing\u003C\/em\u003E \u003Cstrong\u003ERobert E. Tarjan (Princeton)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003ENovember 10\u0026nbsp;- Pettit Microelectronics Building 102 A\u0026amp;B - 11:00AM \u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003ENovember 11\u0026nbsp;- Skiles 005 - 1:00PM\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003ETBA\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003ETBA\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/www.cs.princeton.edu\/~ret\/\u0022\u003ERobert E. Tarjan\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Title:  TBA"}],"uid":"35702","created_gmt":"2022-09-01 15:55:24","changed_gmt":"2022-09-01 15:58:59","author":"mb121","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-11-10T11:00:00-05:00","event_time_end":"2022-11-10T12:41:00-05:00","event_time_end_last":"2022-11-10T12:41:00-05:00","gmt_time_start":"2022-11-10 16:00:00","gmt_time_end":"2022-11-10 17:41:00","gmt_time_end_last":"2022-11-10 17:41:00","rrule":"RRULE:FREQ=DAILY;INTERVAL=1;COUNT=2;WKST=SU","timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"660238":{"#nid":"660238","#data":{"type":"event","title":"ARC Colloquium: Yuansi Chen (Duke University)","body":[{"value":"\u003Cp align =\u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EYuansi Chen (Duke University)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003ESeptember 12, 2022\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E Localization\u0026nbsp;schemes: A framework for proving mixing bounds for Markov chains\u003Cstrong\u003E \u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp;\u0026nbsp;\u003C\/strong\u003EOur work is motivated by two recent and seemingly-unrelated techniques for proving mixing bounds for Markov chains:\u003C\/p\u003E\r\n\r\n\u003Cp\u003E(i) the concept of spectral independence, introduced by Anari, Liu and Oveis Gharan, and its numerous extensions, which have given rise to\u0026nbsp;several breakthroughs in the analysis of mixing times of discrete Markov chains and\u003Cbr \/\u003E\r\n(ii) the stochastic\u0026nbsp;localization\u0026nbsp;technique which has proven useful in establishing mixing and expansion bounds for both log-concave measures and\u0026nbsp;for measures on the discrete hypercube.\u003Cbr \/\u003E\r\n\u0026nbsp;\u003Cbr \/\u003E\r\nIn this work, we present a framework which connects ideas from both techniques and allows us to unify proofs in the mixing time of MCMC\u0026nbsp;algorithms on high dimensional distributions. In its center is the concept of a\u0026nbsp;localization\u0026nbsp;scheme which, to every probability measure , assigns a\u0026nbsp;martingale of probability measures which localize in space as time evolves. This viewpoint provides tools for deriving mixing bounds for the\u0026nbsp;dynamics through the analysis of the corresponding\u0026nbsp;localization\u0026nbsp;process.\u0026nbsp; Generalizations of concepts of spectral independence naturally arise\u0026nbsp;from our definitions. In particular we show via our framework that it is possible to recover the main theorems in the spectral independence\u0026nbsp;frameworks via simple martingale arguments, while completely bypassing the theory of high-dimensional expanders.\u0026nbsp; As applications, we discuss\u0026nbsp;how to use it to obtain the first O(nlogn) bound for mixing time of the hardcore-model (of arbitrary degree) in the tree-uniqueness regime, under\u0026nbsp;Glauber dynamics and to prove a KL-divergence decay bound for log-concave sampling via the Restricted Gaussian Oracle, which achieves\u0026nbsp;optimal mixing under any exp(n)-warm start.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E---------------------------------------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022http:\/\/www2.stat.duke.edu\/~yc443\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003Cem\u003E and \u003Ca href=\u0022http:\/\/arc.gatech.edu\/node\/121\u0022\u003Ehttp:\/\/arc.gatech.edu\/node\/121\u003C\/a\u003E \u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Localization schemes: A framework for proving mixing bounds for Markov chains - Klaus 1116 at 11am"}],"uid":"35702","created_gmt":"2022-08-17 13:45:34","changed_gmt":"2022-08-29 15:30:47","author":"mb121","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-09-12T12:00:00-04:00","event_time_end":"2022-09-12T13:00:00-04:00","event_time_end_last":"2022-09-12T13:00:00-04:00","gmt_time_start":"2022-09-12 16:00:00","gmt_time_end":"2022-09-12 17:00:00","gmt_time_end_last":"2022-09-12 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"660030":{"#nid":"660030","#data":{"type":"event","title":"ARC Colloquium: Jan van den Brand (Georgia Tech)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EJan van den Brand (Georgia Tech)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAugust 29, 2022\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E Fully Dynamic st-Distances \u003Cstrong\u003E \u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003EIn this talk I will present a fully dynamic algorithm for maintaining approximate distances in a graph.\u003Cbr \/\u003E\r\nIn particular, given an unweighted and undirected graph G=(V,E) undergoing edge insertions and deletions, two vertices s,t and a parameter 0\u0026lt;\u03f5\u0026le;1, the dynamic algorithm maintains a (1+\u03f5)-approximation of the st-distance\u0026nbsp; in O(n1.407) time per update (for the current best known bound on the matrix multiplication exponent \u0026omega;).\u003Cbr \/\u003E\r\nAt the core, the approach is to combine algebraic data structures with a graph theoretic technique called emulators. This also leads to novel dynamic algorithms for maintaining (1+\u03f5,\u0026beta;)-emulators that improve upon the state of the art.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E---------------------------------------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/www.ocf.berkeley.edu\/~vdbrand\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003Cem\u003E and \u003Ca href=\u0022http:\/\/arc.gatech.edu\/node\/121\u0022\u003Ehttp:\/\/arc.gatech.edu\/node\/121\u003C\/a\u003E \u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Fully Dynamic st-Distances - Klaus 1116 at 11am"}],"uid":"27544","created_gmt":"2022-08-09 17:58:53","changed_gmt":"2022-08-22 12:18:06","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-08-29T12:00:00-04:00","event_time_end":"2022-08-29T13:00:00-04:00","event_time_end_last":"2022-08-29T13:00:00-04:00","gmt_time_start":"2022-08-29 16:00:00","gmt_time_end":"2022-08-29 17:00:00","gmt_time_end_last":"2022-08-29 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"660254":{"#nid":"660254","#data":{"type":"event","title":"ARC Colloquium: Sinho Chewi (MIT) ","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003ESinho Chewi (MIT)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EOctober 3, 2022\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E TBA\u003Cstrong\u003E \u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003ETBA\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E---------------------------------------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/math.mit.edu\/directory\/profile.php?pid=2107\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003Cem\u003E and \u003Ca href=\u0022http:\/\/arc.gatech.edu\/node\/121\u0022\u003Ehttp:\/\/arc.gatech.edu\/node\/121\u003C\/a\u003E \u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Title TBA: Klaus 1116 at 11am"}],"uid":"35702","created_gmt":"2022-08-17 15:08:13","changed_gmt":"2022-08-18 00:30:54","author":"mb121","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-10-03T12:00:00-04:00","event_time_end":"2022-10-03T13:00:00-04:00","event_time_end_last":"2022-10-03T13:00:00-04:00","gmt_time_start":"2022-10-03 16:00:00","gmt_time_end":"2022-10-03 17:00:00","gmt_time_end_last":"2022-10-03 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"660255":{"#nid":"660255","#data":{"type":"event","title":"ARC Colloquium: Debmalya Panigrahi (Duke University)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EDebmalya Panigrahi (Duke University)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EOctober 10, 2022\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E TBA\u003Cstrong\u003E \u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003ETBA\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E---------------------------------------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/www.debmalyapanigrahi.org\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003Cem\u003E and \u003Ca href=\u0022http:\/\/arc.gatech.edu\/node\/121\u0022\u003Ehttp:\/\/arc.gatech.edu\/node\/121\u003C\/a\u003E \u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Title TBA: Klaus 1116 at 11am"}],"uid":"35702","created_gmt":"2022-08-17 15:13:01","changed_gmt":"2022-08-17 15:13:01","author":"mb121","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-10-10T12:00:00-04:00","event_time_end":"2022-10-10T13:00:00-04:00","event_time_end_last":"2022-10-10T13:00:00-04:00","gmt_time_start":"2022-10-10 16:00:00","gmt_time_end":"2022-10-10 17:00:00","gmt_time_end_last":"2022-10-10 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"660253":{"#nid":"660253","#data":{"type":"event","title":"ARC Colloquium: Rekha R. Thomas (University of Washington)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003ERekha R. Thomas (University\u0026nbsp;of Washington) \u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, September 26, 2022\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116\u0026nbsp;- 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003EGraphical Designs\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EGraphical designs on undirected graphs are discrete analogs of spherical\u0026nbsp;designs. They provide quadrature rules on graphs in the sense that a\u0026nbsp;design consists of a subset of vertices with prescribed weights so\u0026nbsp;that the weighted average of a class of graph functions on these\u0026nbsp;vertices is also the global average of the functions on the\u0026nbsp;graph. Depending on the allowed weights, and class of functions to be\u0026nbsp;averaged, one obtains different types of designs. An important\u0026nbsp;question about designs is how to compute them and optimize over\u003C\/p\u003E\r\n\r\n\u003Cp\u003Ethem. In this talk I will explain how positively weighted designs can\u0026nbsp;be organized on the faces of a polytope and using this\u0026nbsp;connection, one can compute the smallest designs in several families of\u0026nbsp;graphs. Designs also connect to random walks on graphs and other\u0026nbsp;well-studied graph entities.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/sites.math.washington.edu\/~thomas\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003Cem\u003E and\u0026nbsp;\u003C\/em\u003E \u003Cem\u003E\u003Ca href=\u0022http:\/\/arc.gatech.edu\/node\/121\u0022\u003Ehttp:\/\/arc.gatech.edu\/node\/121\u003C\/a\u003E\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Graphical Designs - Klaus 1116 at 11am"}],"uid":"35702","created_gmt":"2022-08-17 15:03:24","changed_gmt":"2022-08-17 15:03:24","author":"mb121","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-09-26T12:00:00-04:00","event_time_end":"2022-09-26T13:00:00-04:00","event_time_end_last":"2022-09-26T13:00:00-04:00","gmt_time_start":"2022-09-26 16:00:00","gmt_time_end":"2022-09-26 17:00:00","gmt_time_end_last":"2022-09-26 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"657432":{"#nid":"657432","#data":{"type":"event","title":"ARC Colloquium: Jerry Li (MSR)","body":[{"value":"\u003Cp\u003ETBA\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"TBA"}],"uid":"36162","created_gmt":"2022-04-19 03:46:25","changed_gmt":"2022-04-19 03:49:12","author":"apillai32","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-04-25T12:00:00-04:00","event_time_end":"2022-04-25T13:00:00-04:00","event_time_end_last":"2022-04-25T13:00:00-04:00","gmt_time_start":"2022-04-25 16:00:00","gmt_time_end":"2022-04-25 17:00:00","gmt_time_end_last":"2022-04-25 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"654516":{"#nid":"654516","#data":{"type":"event","title":"ARC Colloquium: Chandra Chekuri (Univ. of Illinois) ","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EChandra Chekuri (Univ. of Illinois) \u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, April 11, 2022\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 East - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003EDensest Subgraph: Supermodularity, Iterative Peeling, and Flow\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003EThe densest subgraph problem in a graph (DSG), in the simplest form, is the following. Given an undirected graph G = (V, E) find a subset S of vertices that maximizes the ratio |E(S)|\/|S| where E(S) is the set of edges with both endpoints in S. DSG and several of its variants are well-studied in theory and practice and have many applications in data mining and network analysis. We study fast algorithms and structural aspects of DSG via the lens of supermodularity. For this we consider the densest supermodular subset problem (DSS): given a non-negative supermodular function f over a ground set V, maximize f(S)\/|S|.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EFor DSG we describe a simple flow-based algorithm that outputs a (1\u0026minus;\\epsilon)-approximation in deterministic O(m polylog(n)\/\\epsilon) time where m is the number of edges.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EGreedy peeling algorithms have been very popular for DSG and several variants due to their efficiency, empirical performance, and worst-case approximation guarantees. We describe a simple peeling algorithm for DSS and analyze its approximation guarantee in a fashion that unifies several existing results. Boob et al. developed an iterative peeling algorithm for DSG which appears to work very well in practice, and made a conjecture about its convergence to optimality. We affirmatively answer their conjecture, and in fact prove that a natural generalization of their algorithm converges for any supermodular function f; the key to our proof is to consider an LP formulation that is derived via the Lov\u0026aacute;sz extension of a supermodular function which is inspired by the LP relaxation of Charikar that has played an important role in several developments.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThis is joint work with Kent Quanrud and Manuel Torres.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022http:\/\/chekuri.cs.illinois.edu\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003Cem\u003E and\u0026nbsp;\u003C\/em\u003E \u003Cem\u003E\u003Ca href=\u0022http:\/\/arc.gatech.edu\/node\/121\u0022\u003Ehttp:\/\/arc.gatech.edu\/node\/121\u003C\/a\u003E\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Densest Subgraph: Supermodularity, Iterative Peeling, and Flow - Klaus 1116 East at 11am"}],"uid":"27544","created_gmt":"2022-01-18 19:53:19","changed_gmt":"2022-03-24 15:14:06","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-04-11T12:00:00-04:00","event_time_end":"2022-04-11T13:00:00-04:00","event_time_end_last":"2022-04-11T13:00:00-04:00","gmt_time_start":"2022-04-11 16:00:00","gmt_time_end":"2022-04-11 17:00:00","gmt_time_end_last":"2022-04-11 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"653078":{"#nid":"653078","#data":{"type":"event","title":"ARC Colloquium:  Yang Liu (Stanford)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EYang Liu\u0026nbsp; (Stanford)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, March 14, 2022\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u0026nbsp;\u003Cstrong\u003E\u0026nbsp;\u003C\/strong\u003EMaximum Flow and Minimum-Cost Flow in Almost-Linear Time\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E We give an algorithm that computes exact maximum flows and minimum-cost flows on directed graphs with $m$ edges and polynomially bounded integral demands, costs, and capacities in $m^{1+o(1)}$ time. Our algorithm builds the flow through a sequence of $m^{1+o(1)}$ approximate undirected minimum-ratio cycles, each of which is computed and processed in amortized $m^{o(1)}$ time using a dynamic data structure.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EOur framework extends to an algorithm running in $m^{1+o(1)}$ time for computing flows that minimize general edge-separable convex functions to high accuracy. This gives an almost-linear time algorithm for several problems including entropy-regularized optimal transport, matrix scaling, $p$-norm flows, and isotonic regression.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EJoint work with Li Chen, Rasmus Kyng, Richard Peng, Maximilian Probst Gutenberg, and Sushant Sachdeva.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E---------------------------------------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/yangpliu.github.io\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003Cem\u003E and \u003Ca href=\u0022http:\/\/arc.gatech.edu\/node\/121\u0022\u003Ehttp:\/\/arc.gatech.edu\/node\/121\u003C\/a\u003E \u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Maximum Flow and Minimum-Cost Flow in Almost-Linear Time - Klaus 1116 East at 11am"}],"uid":"27544","created_gmt":"2021-11-22 17:34:07","changed_gmt":"2022-03-04 13:34:43","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-03-14T12:00:00-04:00","event_time_end":"2022-03-14T13:00:00-04:00","event_time_end_last":"2022-03-14T13:00:00-04:00","gmt_time_start":"2022-03-14 16:00:00","gmt_time_end":"2022-03-14 17:00:00","gmt_time_end_last":"2022-03-14 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"655642":{"#nid":"655642","#data":{"type":"event","title":" ARC Colloquium: Alex Wein  (Georgia Tech)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003E\u0026nbsp; Alex Wein\u0026nbsp; (Georgia Tech)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, February 28, 2022\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u0026nbsp;\u003Cstrong\u003E\u0026nbsp;\u003C\/strong\u003EStatistical and Computational Phase Transitions on Group Testing\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u0026nbsp; In the group testing problem, the goal is to identify a set of k infected individuals carrying a rare disease within a population of size n, based on pooled tests which pick a random subset of individuals and return positive iff at least one of them is infected. This is a problem of practical importance, and also a good testbed for exploring statistical-computational gaps: How many tests are needed in order to infer the infected individuals from the test results? And how many tests are needed to do so in a computationally-efficient manner?\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\nI will tell the story of a few different frameworks that have been used to understand these questions. Based on a \u0026quot;first moment overlap gap property\u0026quot; calculation and numerical simulations, it was conjectured (but not proven) that a Markov chain Monte Carlo (MCMC) method achieves poly-time reconstruction with the information-theoretically optimal number of tests, that is, there is no statistical-computational gap (Iliopoulos and Zadik, 2020). However, our new results provide contrary evidence: we prove that the class of \u0026quot;low-degree polynomial algorithms\u0026quot; cannot reach the information-theoretic threshold; this suggests that there *is* an inherent stat-comp gap, although we do not formally rule out the MCMC algorithm of [IZ20]. I will discuss some new tools for proving low-degree lower bounds, and give an overview of some of the mysteries and open problems that remain.\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\nBased on joint work with Amin Coja-Oghlan, Oliver Gebhard, Max Hahn-Klimroth, and Ilias Zadik.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E---------------------------------------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/www.alex-wein.com\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Statistical and Computational Phase Transitions in Group Testing - Klaus 1116 at 11am"}],"uid":"36162","created_gmt":"2022-02-21 19:00:07","changed_gmt":"2022-02-22 14:04:20","author":"apillai32","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-02-28T11:00:00-05:00","event_time_end":"2022-02-28T12:00:00-05:00","event_time_end_last":"2022-02-28T12:00:00-05:00","gmt_time_start":"2022-02-28 16:00:00","gmt_time_end":"2022-02-28 17:00:00","gmt_time_end_last":"2022-02-28 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"652416":{"#nid":"652416","#data":{"type":"event","title":"ARC Colloquium: Nikhil Bansal (Univ. of Michigan)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003ENikhil Bansal (Univ. of Michigan)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, February 21, 2022\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 East - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003EMore on the power of two choices in balls and bins\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003EI will describe some recent results on generalizations of the classical two choices model for balls into bins processes.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EOne such generalization is the graphical process where the bins correspond to the vertices of a graph G, and at any time a random edge is picked and a ball must be assigned to one of its end-points.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EAnother extension is where the balls can also be deleted arbitrarily by an oblivious adversary. Interestingly, in both cases the natural greedy strategy can be far from optimal, and I will describe other strategies for these settings that are close to optimal.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EBased on joint works with Ohad Feldheim and William Kuszmaul.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/www.win.tue.nl\/~nikhil\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"More on the power of two choices in balls and bins - Klaus 1116 at 11am"}],"uid":"27544","created_gmt":"2021-11-03 16:52:06","changed_gmt":"2022-02-11 14:57:17","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-02-21T11:00:00-05:00","event_time_end":"2022-02-21T12:00:00-05:00","event_time_end_last":"2022-02-21T12:00:00-05:00","gmt_time_start":"2022-02-21 16:00:00","gmt_time_end":"2022-02-21 17:00:00","gmt_time_end_last":"2022-02-21 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"655069":{"#nid":"655069","#data":{"type":"event","title":"ARC Colloquium: Manolis Vlatakis (Columbia)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EManolis Vlatakis (Columbia)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, February 7, 2022\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EVirtual via BlueJeans - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp;\u003C\/strong\u003E Building Optimization beyond Minimization: A Journey in Game Dynamics\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u0026nbsp; Motivated by recent advances in both theoretical and applied aspects of multiplayer games, spanning from e-sports to multi-agent generative adversarial networks, a surge of different studies\u0026nbsp;have been focused on the core problem of\u0026nbsp;understanding the behavior of game dynamics in general\u0026nbsp;N-player games. From the seminal settings of two competitive players and Min-Max Optimization to the complete\u0026nbsp;understanding of how the day-to-day behavior of the dynamics correlates to the game\u0026#39;s different notion of equilibria is much more limited, and only partial results are known for certain classes of games (such as zero-sum or congestion games). In this talk, we study from two different perspectives\u0026nbsp;arguably the most well-studied class of no-regret dynamics, \u0026quot;Follow-the-regularized-leader\u0026quot; (FTRL) and Discretizations of Gradient Flow (GDA\/OGDA\/EG), \u0026nbsp;and we establish a sweeping negative result showing that the notion of mixed Nash equilibrium is antithetical to no-regret learning. Specifically, we show that any Nash equilibrium which is not strict (in that every player has a unique best response) cannot be stable and attracting under the dynamics of FTGL. This result has significant implications for predicting the outcome of a learning process as it shows unequivocally that only strict (and hence, pure) Nash equilibria can emerge as stable limit points thereof. For a final happy end story, we present either structural examples of families where convergence is possible providing the last-iterate convergence rates or even new methods inspired from other areas like control theory \u0026amp; planning.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EBio:\u003Cbr \/\u003E\r\nEmmanouil (Manolis) V. Vlatakis Gkaragkounis is a final year PhD student in the Department of Computer Science at Columbia University, under the supervision of prof. Mihalis Yannakakis and Rocco Servedio. Currently, he is Simons-Google Research fellow at the University of California at Berkeley.\u0026nbsp;Before joining Columbia University, he interned at \u0026quot;Athena\u0026quot; Research \u0026amp; Innovation Center in Athens, Greece. He received his integrated B.s \u0026amp; M.s in ECE Department of National Technical University of Athens, where he was advised by Dimitris Fotakis. Manolis\u0026#39;s primary interest is in the intersection of Theoretical Computer Science \u0026amp; Machine Learning, with a particular focus in\u0026nbsp;Algorithmic Game Theory, Optimization, Computational Complexity and Beyond Worst-case Analysis of Algorithms .\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022http:\/\/www.cs.columbia.edu\/~emvlatakis\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":" Building Optimization beyond Minimization: A Journey in Game Dynamics - Virtual via BlueJeans at 11am"}],"uid":"27544","created_gmt":"2022-02-02 16:30:31","changed_gmt":"2022-02-04 18:17:18","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-02-07T11:00:00-05:00","event_time_end":"2022-02-07T12:00:00-05:00","event_time_end_last":"2022-02-07T12:00:00-05:00","gmt_time_start":"2022-02-07 16:00:00","gmt_time_end":"2022-02-07 17:00:00","gmt_time_end_last":"2022-02-07 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"652418":{"#nid":"652418","#data":{"type":"event","title":"ARC-ACO Lecture Series:  featuring Pravesh Kothari (CMU)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EARC - ACO Lecture Series\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cem\u003Efeaturing\u003C\/em\u003E \u003Cstrong\u003EPravesh Kothari (CMU)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EFebruary 15 \u0026amp; 17 - Groseclose 402 - 11:00AM \u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EFebruary 18 - Groseclose 402 - 1:00PM\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003EHigh-Dimensional Statistical Estimation via Sum-of-Squares\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003EOne exciting new development of the past decade is the\u0026nbsp;evolution of the sum-of-squares method for algorithm design for high-dimensional statistical estimation. This paradigm can be viewed as a principled approach to\u0026nbsp;generating and analyzing semidefinite programming relaxations for statistical estimation problems by thinking of the duals as \u003Cem\u003Eproofs of statistical identifiability\u003C\/em\u003E\u0026nbsp;-- i.e., proof that the input data uniquely identifies the unknown target parameters.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIn this sequence of three lectures, I will give an overview of the sum-of-squares method for statistical estimation. Specifically, I will discuss how strengthening\u0026nbsp;(via semidefinite certificates) of basic analytic properties of probability distributions such as subgaussian tails, hypercontractive moments, and anti-concentration yield new algorithms for problems such as learning spherical and non-spherical Gaussian mixture models and basic tasks in algorithmic robust statistics.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EBio:\u0026nbsp; \u003C\/strong\u003EPravesh Kothari is an Assistant Professor in the Computer Science Department at CMU. He is broadly interested in algorithms and algorithmic thresholds for average-case computational problems with a specific focus on\u0026nbsp;problems at the intersection of theoretical computer science and statistics. His prior work has focused on developing the Sum-of-Squares method for algorithm design leading to progress on problems such as learning mixtures of Gaussians, refuting random constraint\u0026nbsp;satisfaction problems, and problems in algorithmic robust statistics.\u0026nbsp; His research has been recognized with a Google Research Scholar Award and an NSF Career Award.\u0026nbsp;\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/www.cs.cmu.edu\/~praveshk\/\u0022\u003EPravesh Kothari\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"High-Dimensional Statistical Estimation via Sum-of-Squares - Groseclose 402 11:00AM"}],"uid":"27544","created_gmt":"2021-11-03 17:07:19","changed_gmt":"2022-02-02 20:38:20","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-02-15T11:00:00-05:00","event_time_end":"2022-02-15T11:00:00-05:00","event_time_end_last":"2022-02-15T11:00:00-05:00","gmt_time_start":"2022-02-15 16:00:00","gmt_time_end":"2022-02-15 16:00:00","gmt_time_end_last":"2022-02-15 16:00:00","rrule":"RRULE:FREQ=DAILY;INTERVAL=1;COUNT=3;WKST=SU\r\nEXDATE:20220216T050000Z","timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"655090":{"#nid":"655090","#data":{"type":"event","title":" ARC Colloquium: Kiran Shiragur  (Stanford)","body":[{"value":"\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003E\u0026nbsp; Kiran Shiragur\u0026nbsp; (Stanford)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EFriday, February 11, 2022\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EVirtual via BlueJeans - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003ETitle:\u0026nbsp;\u003Cstrong\u003EEfficient universal estimators for symmetric property estimation\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EAbstract:\u0026nbsp;Given i.i.d samples from an unknown distribution, estimating its symmetric properties is a classical problem in information theory, statistics and computer science. Symmetric properties are those that are invariant to label permutations and include popular functionals such as entropy and support size. Early work on this question dates back to the 1940s when R. A. Fisher and A. S. Corbet studied this to estimate the number of distinct butterfly species in Malaysia. Over the past decade, this question has received great attention leading to computationally efficient and sample optimal estimators for various symmetric properties. All these estimators were property specific and the design of a single estimator that is sample optimal for any symmetric property remained a central open problem in the area.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIn a recent breakthrough, Acharya et. al. showed that computing an approximate profile maximum likelihood (PML), a distribution that maximizes the likelihood of the observed multiset of frequencies, allows statistically optimal estimation of any symmetric property. However, since its introduction by Orlitsky et. al. in 2004, efficient computation of an approximate PML remained a well known open problem.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIn our work, we resolved this question by designing the first efficient algorithm for computing an approximate PML distribution. In addition, our investigations have led to a deeper understanding of various computational and statistical aspects of PML and universal estimators.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E---------------------------------------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/sites.google.com\/view\/kiran-shiragur\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Efficient universal estimators for symmetric property estimation- Virtual via Bluejeans"}],"uid":"34983","created_gmt":"2022-02-02 19:20:41","changed_gmt":"2022-02-02 19:20:41","author":"Mohit Singh","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-02-11T11:00:00-05:00","event_time_end":"2022-02-11T12:00:00-05:00","event_time_end_last":"2022-02-11T12:00:00-05:00","gmt_time_start":"2022-02-11 16:00:00","gmt_time_end":"2022-02-11 17:00:00","gmt_time_end_last":"2022-02-11 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"652155":{"#nid":"652155","#data":{"type":"event","title":"ARC Colloquium:David Gamarnik (MIT)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EDavid Gamarnik (MIT)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, February 14, 2022\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 East - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003EOverlap gap property: A topological barrier to optimizing over random structures\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003EMany decision and optimization problems over random structures exhibit a gap between the existential and algorithmically achievable values. Examples include the problem of finding a largest independent set in a random graph, the problem of finding a near ground state in a spin glass model, the problem of finding a satisfying assignment in a random constraint satisfaction problem, and many many more. At the same time, no formal computational hardness of these problems exists which would explain this persistent algorithmic gap.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIn the talk we will describe a new approach for establishing an algorithmic intractability for these problems called the overlap gap property. Originating in statistical physics, and specifically in the theory of spin glasses, this is a simple to describe property which a) emerges in most models known to exhibit an apparent algorithmic hardness; b) is consistent with the hardness\/tractability phase transition for many models analyzed to the day; and, importantly, c) allows to mathematically rigorously rule out a large class of algorithms as potential contenders, specifically the algorithms which exhibit the input stability (noise insensitivity).\u003C\/p\u003E\r\n\r\n\u003Cp\u003EWe will specifically show how to use this property to obtain stronger than the state of the art lower bounds on the depth of Boolean circuits for solving two of the aforementioned problems: the problem of finding a large independent set in a sparse random graph, and the problem of finding a near ground state of a p-spin model.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022http:\/\/www.mit.edu\/~gamarnik\/home.html\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Overlap gap property: A topological barrier to optimizing over random structures - Klaus 1116 at 11am"}],"uid":"27544","created_gmt":"2021-10-27 18:54:42","changed_gmt":"2022-02-01 16:34:48","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-02-14T11:00:00-05:00","event_time_end":"2022-02-14T12:00:00-05:00","event_time_end_last":"2022-02-14T12:00:00-05:00","gmt_time_start":"2022-02-14 16:00:00","gmt_time_end":"2022-02-14 17:00:00","gmt_time_end_last":"2022-02-14 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"654821":{"#nid":"654821","#data":{"type":"event","title":"ARC Colloquium: Bento Natura (LSE)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EBento Natura (LSE)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EFriday, January 28, 2022\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EVirtual via BlueJeans - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003E Fast Exact Solvers for Linear Programs via Interior Point Methods\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003ERecent years have seen tremendous progress in approximate solvers for Linear Programs (LP) based on Interior-Point Methods (IPM). In this talk we show how to leverage these algorithms to design algorithms that solve LPs exactly. The running time of these algorithms depends on the constraint matrix only. We will present these algorithms in two different regimes: In the first, we use approximate LP solvers in a blackbox manner, extending Tardos\u0026rsquo;s Framework (Oper. Res. \u0026rsquo;86). In the second, we design an exact IPM, using ideas of the recent approximate IPMs to improve the running time.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/personal.lse.ac.uk\/natura\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Fast Exact Solvers for Linear Programs via Interior Point Methods - Virtual via BlueJeans at 11:00am"}],"uid":"27544","created_gmt":"2022-01-26 21:08:39","changed_gmt":"2022-01-26 21:08:39","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-01-28T11:00:00-05:00","event_time_end":"2022-01-28T12:00:00-05:00","event_time_end_last":"2022-01-28T12:00:00-05:00","gmt_time_start":"2022-01-28 16:00:00","gmt_time_end":"2022-01-28 17:00:00","gmt_time_end_last":"2022-01-28 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"654736":{"#nid":"654736","#data":{"type":"event","title":"ARC Colloquium\/ACO Student Seminar: Ziv Scully (CMU)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u0026nbsp;\u003C\/strong\u003E\u003Cstrong\u003E \u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EZiv Scully (CMU)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EFriday, February 4, 2022\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EVirtual via BlueJeans - 1:00 pm\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003EA New Toolbox for Scheduling Theory\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003EQueueing delays are ubiquitous in many domains, including computer systems, service systems, communication networks, supply chains, and transportation. Queueing and scheduling theory provide a rigorous basis for understanding how to reduce delays with scheduling, including evaluating policy performance and guiding policy design. Unfortunately, state-of-the-art theory fails to address many practical concerns. For example, scheduling theory seldom treats nontrivial preemption limitations, and there is very little theory for scheduling in multiserver queues.\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\nWe present two new, broadly applicable tools that greatly expand the reach of scheduling theory, using each to solve multiple open problems. The first tool, called \u0026ldquo;SOAP\u0026rdquo;, is a new unifying theory of scheduling in single-server queues, specifically the M\/G\/1 model. SOAP characterizes the delay distribution of a broad space of policies, most of which have never been analyzed before. Such policies include the Gittins index policy, which minimizes mean delay in low-information settings, and many policies with preemption limitations. The second tool, called \u0026ldquo;WINE\u0026rdquo;, is a new queueing identity that complements Little\u0026rsquo;s law. WINE enables a new method of analyzing complex queueing systems by relating them to simpler systems. This results in the first delay bounds for SRPT (shortest remaining processing time) and the Gittins index policy in multiserver queues, specifically the M\/G\/k model.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/ziv.codes\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"A New Toolbox for Scheduling Theory - Virtual via BlueJeans at 1:00pm"}],"uid":"27544","created_gmt":"2022-01-24 20:27:42","changed_gmt":"2022-01-25 19:51:57","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-02-04T13:00:00-05:00","event_time_end":"2022-02-04T14:00:00-05:00","event_time_end_last":"2022-02-04T14:00:00-05:00","gmt_time_start":"2022-02-04 18:00:00","gmt_time_end":"2022-02-04 19:00:00","gmt_time_end_last":"2022-02-04 19:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"654683":{"#nid":"654683","#data":{"type":"event","title":"ARC Colloquium: Ainesh Bakshi (CMU)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAinesh Bakshi (CMU)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, January 31, 2022\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EVirtual via BlueJeans - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003EAnalytic Techniques for Robust Algorithm Design\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003EModern machine learning relies on algorithms that fit expressive models to large datasets. While such tasks are easy in low dimensions, real-world datasets are truly high-dimensional. Additionally, a prerequisite to deploying models in real-world systems is to ensure that their behavior degrades gracefully when the modeling assumptions no longer hold. Therefore, there is a growing need for\u0026nbsp;\u003Cem\u003Eefficient algorithms\u003C\/em\u003E\u0026nbsp;that fit reliable and robust models to data.\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\nIn this talk, I will provide an overview of designing such efficient and robust algorithms, with provable guarantees, for fundamental tasks in machine learning and statistics. In particular, I will describe two complementary themes arising in this area:\u0026nbsp;\u003Cem\u003Ehigh-dimensional robust statistics\u003C\/em\u003E\u0026nbsp;and\u0026nbsp;\u003Cem\u003Efast numerical linear algebra\u003C\/em\u003E. The first addresses how to fit expressive models to high-dimensional datasets in the presence of outliers and the second develops fast algorithmic primitives to reduce dimensionality and de-noise large datasets. I will focus on recent results on robustly\u0026nbsp;learning mixtures of arbitrary Gaussians and describe the new algorithmic ideas obtained along the way. Finally, I will make the case for analytic techniques, such as convex relaxations, being the natural choice for robust algorithm design.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022http:\/\/aineshbakshi.com\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Analytic Techniques for Robust Algorithm Design - Virtual via BlueJeans at 11am"}],"uid":"27544","created_gmt":"2022-01-21 20:52:15","changed_gmt":"2022-01-24 20:43:02","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-01-31T11:00:00-05:00","event_time_end":"2022-01-31T12:00:00-05:00","event_time_end_last":"2022-01-31T12:00:00-05:00","gmt_time_start":"2022-01-31 16:00:00","gmt_time_end":"2022-01-31 17:00:00","gmt_time_end_last":"2022-01-31 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"653431":{"#nid":"653431","#data":{"type":"event","title":"CANCELLED: ARC Colloquium: Divyarthi Mohan (Tel Aviv University)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp  align = \u0022center\u0022\u003E\u003Cstrong\u003EDivyarthi Mohan (Tel Aviv University)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp  align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, January 10, 2022\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp  align = \u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003ESimplicity and Optimality in Multi-Item Auctions\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003EDesigning mechanisms to maximize revenue is a fundamental problem in mathematical economics and has various applications like online ad auctions and spectrum auctions. Unfortunately, optimal auctions for selling multiple items can be unreasonably complex and computationally intractable. In this talk, we consider a revenue-maximizing seller with n items facing a single unit-demand buyer. Our work shows that simple mechanisms can achieve almost optimal revenue. We approached the tradeoffs of simplicity formally through the lens of computation and menu size. Our main result provides a mechanism that gets a (1 \u0026minus; \u0026epsilon;)-approximation to the optimal revenue in time quasi-polynomial in n and has quasi polynomial (symmetric) menu complexity.\u003Cbr \/\u003E\r\n\u0026nbsp;\u003Cbr \/\u003E\r\nJoint work with Pravesh Kothari, Ariel Schvartzman, Sahil Singla, and Matt Weinberg.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/divyarthi.github.io\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Simplicity and Optimality in Multi-Item Auctions - Klaus 1116 at 11am"}],"uid":"27544","created_gmt":"2021-12-06 18:31:54","changed_gmt":"2022-01-10 14:13:52","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-01-10T11:00:00-05:00","event_time_end":"2022-01-10T12:00:00-05:00","event_time_end_last":"2022-01-10T12:00:00-05:00","gmt_time_start":"2022-01-10 16:00:00","gmt_time_end":"2022-01-10 17:00:00","gmt_time_end_last":"2022-01-10 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"651573":{"#nid":"651573","#data":{"type":"event","title":"ThinkTankTalk: Nick Sahinidis (Georgia Tech)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC) \u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EThinkTankTalk\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003ENick Sahindis (Georgia Tech)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, November 15, 2021\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle: \u003C\/strong\u003EOpen problems in protein folding and other molecular challenges\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003EThe purpose of this talk is to describe a number of open optimization problems related to the prediction of molecular conformations. We first review protein folding and AlphaFold, molecular docking, and drug design. Then, we present a number of related optimization problems that are open. Our ability to solve these problems stands to benefit from:\u003C\/p\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EClosed-form expressions of convex envelopes of nonconvex functions,\u003C\/li\u003E\r\n\t\u003Cli\u003ETechniques for dealing with symmetries in continuous optimization formulations, and\u003C\/li\u003E\r\n\t\u003Cli\u003ETight bounds on distances between particles in 3D based on optimality and geometric considerations.\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/www.isye.gatech.edu\/users\/nsahinidis\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Open problems in protein folding and other molecular challenges - Klaus 1116 at 11am"}],"uid":"27544","created_gmt":"2021-10-11 14:22:59","changed_gmt":"2021-11-08 16:44:54","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2021-11-15T11:00:00-05:00","event_time_end":"2021-11-15T12:00:00-05:00","event_time_end_last":"2021-11-15T12:00:00-05:00","gmt_time_start":"2021-11-15 16:00:00","gmt_time_end":"2021-11-15 17:00:00","gmt_time_end_last":"2021-11-15 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"649243":{"#nid":"649243","#data":{"type":"event","title":"ARC Colloquium: Kamesh Munagala (Duke University)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKamesh Munagala (Duke University)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, November 8, 2021\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EGroseclose 402 - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003EGroup Fairness in Network Design and Combinatorial Optimization\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003EConsider the following classical network design model. There are n clients in a multi-graph with a single sink node. Each edge has a cost to buy, and a length if bought; typically, costlier edges have smaller lengths. There is a budget B on the total cost of edges bought. Given a set of bought edges, the distance of a client to the sink is the shortest path according to the edge lengths. Such a model captures buy-at-bulk network design and facility location as special cases.\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\nRather than pose this as a standard optimization problem, we ask a different question: Suppose a provider is allocating budget B to build this network, how should it do so in a manner that is fair to the clients? We consider a classical model of group fairness termed the core in cooperative game theory: If each client contributes its share B\/n amount of budget as tax money, no subset of clients should be able to pool their tax money to deviate and build a different network that simultaneously improves all their distances to the sink. The question is: Does such a solution always exist, or approximately exist?\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\nWe consider an abstract \u0026ldquo;committee selection\u0026rdquo; model from social choice literature that captures not only the above problem, but other combinatorial optimization problems where we need to provision public resources subject to combinatorial constraints, in order to provide utility to clients. For this general model, we show that an approximately fair solution always exists, where the approximation scales down the tax money each client can use for deviation by only a constant factor. Our existence result relies on rounding an interesting fractional relaxation to this problem. In certain cases such as the facility location problem, it also implies a polynomial time algorithm. We also show that similar results when the approximation is on the utility that clients derive by deviating.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/www.kameshmunagala.org\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Group Fairness in Network Design and Combinatorial Optimization - Groseclose 402 at 11am"}],"uid":"27544","created_gmt":"2021-08-04 13:13:41","changed_gmt":"2021-10-25 12:13:10","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2021-11-08T11:00:00-05:00","event_time_end":"2021-11-08T12:00:00-05:00","event_time_end_last":"2021-11-08T12:00:00-05:00","gmt_time_start":"2021-11-08 16:00:00","gmt_time_end":"2021-11-08 17:00:00","gmt_time_end_last":"2021-11-08 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"651572":{"#nid":"651572","#data":{"type":"event","title":"ARC Colloquium: Vidya  Muthukumar (Georgia Tech)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EVidya Muthukumar (Georgia Tech)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, October 25, 2021\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EGroseclose 402 - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003ESurprises in high-dimensional linear classification\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003ESeemingly counter-intuitive phenomena in deep neural networks and kernel methods have prompted a recent re-investigation of classical machine learning methods, like linear models. Of particular focus is sufficiently high-dimensional setups in which\u0026nbsp;\u003Cem\u003Einterpolation\u003C\/em\u003E\u0026nbsp;of training data is possible. In this talk, we will first briefly review recent works showing that zero regularization, or fitting of noise, need not be harmful in regression tasks. Then, we will use this insight to uncover two new surprises for high-dimensional linear classification:\u003C\/p\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003Eleast-2-norm interpolation can classify consistently even when the corresponding regression task fails, and\u003C\/li\u003E\r\n\t\u003Cli\u003Ethe support-vector-machine and least-2-norm interpolation solutions \u003Cem\u003Eexactly coincide\u003C\/em\u003E in sufficiently high-dimensional linear model.\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Cp\u003EThese findings taken together imply that the linear SVM can generalize well in settings beyond those predicted by training-data-dependent complexity measures.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThis is joint work with Misha Belkin, Daniel Hsu, Adhyyan Narang, Anant Sahai, Vignesh Subramanian, Christos Thrampoulidis, Ke Wang and Ji Xu.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/www.isye.gatech.edu\/users\/vmuthukumar\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Surprises in high-dimensional linear classification - Groseclose 402 at 11am"}],"uid":"27544","created_gmt":"2021-10-11 14:14:28","changed_gmt":"2021-10-19 16:29:20","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2021-10-25T12:00:00-04:00","event_time_end":"2021-10-25T13:00:00-04:00","event_time_end_last":"2021-10-25T13:00:00-04:00","gmt_time_start":"2021-10-25 16:00:00","gmt_time_end":"2021-10-25 17:00:00","gmt_time_end_last":"2021-10-25 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"648987":{"#nid":"648987","#data":{"type":"event","title":"ARC Colloquium: Aaron Sidford (Stanford)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAaron Sidford (Stanford)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, October 4, 2021\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 East - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003ERecent Advances on the Maximum Flow Problem\u003Cem\u003E \u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003EThe maximum flow problem is an incredibly well-studied problem in combinatorial optimization. The problem encompasses a range of cut, matching, and scheduling problems and is a key a proving ground for new techniques in continuous optimization and algorithmic graph theory. In this talk I will survey recent, provably faster algorithms for solving this problem. Further, I will highlight how recent advances in solving mixed l2-lp flows can be coupled with interior point methods to obtain improved running times for solving the problem on unit-capacity graphs. The maximum flow problem on unit capacity graphs encompasses fundamental combinatorial optimization problems including bipartite matching and computing disjoint paths and I will discuss how this line of work has led to state-of-the-art, almost m^(4\/3) time algorithms for solving these problems on m-edge graphs. This talk focuses on joint work with Yang P. Liu and Tarun Kathuria.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/web.stanford.edu\/~sidford\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Recent Advances on the Maximum Flow Problem - Klaus 1116 East at 11am"}],"uid":"27544","created_gmt":"2021-07-22 14:52:44","changed_gmt":"2021-09-28 13:46:39","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2021-10-04T12:00:00-04:00","event_time_end":"2021-10-04T13:00:00-04:00","event_time_end_last":"2021-10-04T13:00:00-04:00","gmt_time_start":"2021-10-04 16:00:00","gmt_time_end":"2021-10-04 17:00:00","gmt_time_end_last":"2021-10-04 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"648989":{"#nid":"648989","#data":{"type":"event","title":"ARC Colloquium: Anupam Gupta (CMU)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAnupam Gupta (CMU)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, October 18, 2021\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 East - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003E Finding and Counting k-cuts in Graphs\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003EFor an undirected graph with edge weights, a k-cut is a set of edges whose deletion breaks the graph into at least k connected components. How fast can we find a minimum-weight k-cut? And how many minimum k-cuts can a graph have? The two problems are closely linked. In 1996 Karger and Stein showed how to find a minimum k-cut in approximately n^{2k-2} time; their proof also bounded the number of minimum k-cuts by n^{2k-2}, using the probabilistic method. Prior\u0026nbsp;to our work, these were the best results known. Moreover, both these\u0026nbsp;results were not known to be tight, except for the case of k=2 (which is the classical problem of finding graph min-cuts).\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIn this talk, we show how both these results can be improved to approximately n^k. We discuss how extremal bounds for set systems, plus a refined analysis of the Karger\u0026#39;s contraction algorithm, can give near-optimal bounds.\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\nThis is joint work with Euiwoong Lee (U.Michigan), Jason Li (CMU), and David Harris (Maryland).\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/csd.cmu.edu\/people\/faculty\/anupam-gupta\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Finding and Counting k-cuts in Graphs - Klaus 1116 East at 11am"}],"uid":"27544","created_gmt":"2021-07-22 15:20:37","changed_gmt":"2021-09-24 13:04:43","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2021-10-18T12:00:00-04:00","event_time_end":"2021-10-18T13:00:00-04:00","event_time_end_last":"2021-10-18T13:00:00-04:00","gmt_time_start":"2021-10-18 16:00:00","gmt_time_end":"2021-10-18 17:00:00","gmt_time_end_last":"2021-10-18 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"650525":{"#nid":"650525","#data":{"type":"event","title":"ARC Seminar: Jan van den Brand (Simons-Berkeley)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EJan van den Brand (Simons-Berkeley)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EWednesday, September 22, 2021\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 East - 3:00 pm\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003EFrom Interior Point Methods to Data Structures and Back\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003ELinear Programs (LPs) capture many optimization problems such as shortest paths or bipartite matching. In the past years, there have been substantial improvements for LP solvers, resulting in algorithms that run in nearly linear time for dense LPs. This also led to a nearly linear time algorithm for bipartite matching on dense graphs. In this talk, I will explain how these improvements stem from an interplay of interior point methods and dynamic algorithms (data structures).\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/www.ocf.berkeley.edu\/~vdbrand\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"From Interior Point Methods to Data Structures and Back - Klaus 1116 East at 3:00pm"}],"uid":"27544","created_gmt":"2021-09-07 14:54:58","changed_gmt":"2021-09-10 12:22:08","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2021-09-22T16:00:00-04:00","event_time_end":"2021-09-22T17:00:00-04:00","event_time_end_last":"2021-09-22T17:00:00-04:00","gmt_time_start":"2021-09-22 20:00:00","gmt_time_end":"2021-09-22 21:00:00","gmt_time_end_last":"2021-09-22 21:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"648986":{"#nid":"648986","#data":{"type":"event","title":"ARC Colloquium:  Ilias Diakonikolas (UW Madison)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EIlias Diakonikolas (UW Madison)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, September 20, 2021\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 East - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003ELearning with Massart Noise\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003EWe study the classical problem of learning halfspaces in the presence of Massart (or bounded) noise. In the Massart model, an adversary can flip the label of each example independently with probability at most $eta\u0026lt;1\/2$. The goal of the learner is to find a hypothesis with small misclassification error. Characterizing the efficient learnability of halfspaces in the Massart model has been a longstanding open question in learning theory, posed in various works, starting with Sloan (1988), Cohen (1997), and highlighted in Avrim Blum\u0026rsquo;s FOCS 2003 tutorial.\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\nIn this talk, we will survey two recent results that resolve this question. We will start by describing the first polynomial-time learning algorithm for Massart halfspaces with non-trivial error guarantees. We will then complement this upper bound with a Statistical Query lower bound, establishing that the error guarantee achieved by our algorithm is essentially optimal. Our findings highlight the algorithmic possibilities and limitations of distribution-free robustness with respect to natural semi-random noise models.\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\nThe talk will primarily be based on joint works with Themis Gouleakis and Christos Tzamos; and with Daniel Kane.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022http:\/\/www.iliasdiakonikolas.org\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Learning with Massart Noise - Klaus 1116 East at 11am"}],"uid":"27544","created_gmt":"2021-07-22 14:47:47","changed_gmt":"2021-08-25 13:01:37","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2021-09-20T12:00:00-04:00","event_time_end":"2021-09-20T13:00:00-04:00","event_time_end_last":"2021-09-20T13:00:00-04:00","gmt_time_start":"2021-09-20 16:00:00","gmt_time_end":"2021-09-20 17:00:00","gmt_time_end_last":"2021-09-20 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"643992":{"#nid":"643992","#data":{"type":"event","title":"ThinkTankTalk: Arijit Raychowdhury (Georgia Tech)","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC) \u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EThinkTankTalk\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EArijit Raychowdhury (Georgia Tech)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EMonday, March 8, 2021\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EVirtual via Bluejeans - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle: \u003C\/strong\u003EComputing with Hardware Accelerated Dynamical Systems\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003ECollective dynamical systems offer unique opportunities for computing by harnessing the complex interactions of simple elements such as oscillators or spike generators. This is possible, when such dynamics can be programmed, controlled, and observed. In this talk, I will discuss some of our work where we are exploring the time-evolution of both deterministic and stochastic dynamical systems in both CMOS and post-CMOS computing substrates. I will show applications of such systems in solving inverse problems and optimizations.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/www.ece.gatech.edu\/faculty-staff-directory\/arijit-raychowdhury\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022http:\/\/arc.gatech.edu\/node\/121\u0022\u003Ehttp:\/\/arc.gatech.edu\/node\/121\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Title Computing with Hardware Accelerated Dynamical Systems-Virtual via Bluejeans at 11:00am"}],"uid":"27544","created_gmt":"2021-02-08 18:57:33","changed_gmt":"2021-06-30 15:54:55","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2021-03-08T11:00:00-05:00","event_time_end":"2021-03-09T11:59:00-05:00","event_time_end_last":"2021-03-09T11:59:00-05:00","gmt_time_start":"2021-03-08 16:00:00","gmt_time_end":"2021-03-09 16:59:00","gmt_time_end_last":"2021-03-09 16:59:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"645460":{"#nid":"645460","#data":{"type":"event","title":"ARC Colloquium:  Ashwin Pananjady (Georgia Tech)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC) \u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAshwin Pananjady (Georgia Tech)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, April 26, 2021\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EVirtual via Bluejeans - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003EToward instance-optimal policy evaluation: From lower bounds to algorithms\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003EThe paradigm of reinforcement learning has now made inroads in a wide range of applied problem domains. This empirical research has revealed the limitations of our theoretical understanding: popular RL algorithms exhibit a variety of behavior across domains and problem instances, and existing theoretical bounds, which are generally based on worst-case assumptions, can often produce pessimistic predictions. An important theoretical goal is to develop instance-specific analyses that help to reveal what aspects of a given problem make it \u0026quot;easy\u0026quot; or \u0026quot;hard\u0026quot;, and allow distinctions to be drawn between ostensibly similar algorithms.\u0026nbsp;Taking an approach grounded in nonparametric statistics, we initiate a study of this question for the policy evaluation problem. We show via information-theoretic lower bounds that many popular variants of temporal difference (TD) learning algorithms *do not* exhibit the optimal instance-specific performance in the finite-sample regime. On the other hand, making careful modifications to these algorithms does result in automatic adaptation to the intrinsic difficulty of the problem. When there is function approximation involved, our bounds also characterize the instance-optimal tradeoff between \u0026quot;bias\u0026quot; and \u0026quot;variance\u0026quot; in solving\u0026nbsp;projected fixed-point equations, a general class of problems that includes policy evaluation as a special case.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThe talk is based on joint work with Koulik Khamaru, Wenlong Mou, Feng Ruan, Martin Wainwright, and Michael Jordan.\u0026nbsp;No prior knowledge of reinforcement learning will be assumed.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/www.isye.gatech.edu\/users\/ashwin-pananjady-martin\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022http:\/\/arc.gatech.edu\/node\/121\u0022\u003Ehttp:\/\/arc.gatech.edu\/node\/121\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Toward instance-optimal policy evaluation: From lower bounds to algorithms - Virtual via Bluejeans at 11:00am"}],"uid":"27544","created_gmt":"2021-03-17 14:17:51","changed_gmt":"2021-04-21 12:00:42","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2021-04-26T12:00:00-04:00","event_time_end":"2021-04-26T13:00:00-04:00","event_time_end_last":"2021-04-26T13:00:00-04:00","gmt_time_start":"2021-04-26 16:00:00","gmt_time_end":"2021-04-26 17:00:00","gmt_time_end_last":"2021-04-26 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"643480":{"#nid":"643480","#data":{"type":"event","title":"ARC Colloquium: Shalev Ben-David (Univ. of Waterloo)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC) \u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EShalev Ben-David (Univ. of Waterloo)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, April 19, 2021\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EVirtual via Bluejeans - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle: \u003C\/strong\u003EForecasting Algorithms, Minimax Theorems, and Randomized Lower Bounds\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003EI will present a new approach to randomized lower bounds, particularly in the setting where we wish to give a fine-grained analysis of randomized algorithms that achieve small bias. The approach is as follows: instead of considering ordinary randomized algorithms which give an output in {0,1} and may err, we switch models to look at \u0026quot;forecasting\u0026quot; randomized algorithms which output a confidence in [0,1] for whether they think the answer is 1. When scored by a proper scoring rule, the performance of the best forecasting algorithm is closely related to the bias of the best (ordinary) randomized algorithm, but is more amenable to analysis.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EAs an application, I\u0026#39;ll present a new\u0026nbsp;minimax\u0026nbsp;theorem for randomized algorithms, which can be viewed as a strengthening of Yao\u0026#39;s\u0026nbsp;minimax\u0026nbsp;theorem. Yao\u0026#39;s\u0026nbsp;minimax\u0026nbsp;theorem guarantees the existence of a hard distribution for a function f such that solving f against this distribution (to a desired error level) is as hard as solving f in the worst case (to that same error level). However, the hard distribution provided by Yao\u0026#39;s theorem depends on the chosen error level. Our\u0026nbsp;minimax\u0026nbsp;theorem removes this dependence, giving a distribution which certifies the hardness of f against all bias levels at once. In recent work, we used this\u0026nbsp;minimax\u0026nbsp;theorem to give a tight composition theorem for randomized query complexity.\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\nBased on joint work with Eric Blais.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/cs.uwaterloo.ca\/people-profiles\/shalev-ben-david\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022http:\/\/arc.gatech.edu\/node\/121\u0022\u003Ehttp:\/\/arc.gatech.edu\/node\/121\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Forecasting Algorithms, Minimax Theorems, and Randomized Lower Bounds - Virtual via Bluejeans at 11:00am"}],"uid":"27544","created_gmt":"2021-01-27 15:00:58","changed_gmt":"2021-04-09 11:55:37","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2021-04-19T12:00:00-04:00","event_time_end":"2021-04-19T13:00:00-04:00","event_time_end_last":"2021-04-19T13:00:00-04:00","gmt_time_start":"2021-04-19 16:00:00","gmt_time_end":"2021-04-19 17:00:00","gmt_time_end_last":"2021-04-19 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"646102":{"#nid":"646102","#data":{"type":"event","title":"ARC Seminar: Timothy Chu (CMU)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EARC Seminar \u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003ETimothy Chu (CMU)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003ETuesday, April 6, 2021\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EVirtual via Bluejeans - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003EManhattan Distances, Kernels, and Metric Transforms\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003ETake n points in any dimension, compute the Manhattan distance between each pair of points, and take the cube root of each distance. The resulting distances are guaranteed to be a Manhattan distance! Can you prove why?\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\nIn this talk, we prove this result and find a full classification of functions that transform Manhattan distances to Manhattan distances. This work involves group symmetry, matrix eigenvalues, and machine learning kernels. No special background will be needed to enjoy this talk!\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\nJoint work with Gary Miller, Shyam Narayanan, and Mark Sellke.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/timchu.github.io\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022http:\/\/arc.gatech.edu\/node\/121\u0022\u003Ehttp:\/\/arc.gatech.edu\/node\/121\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Manhattan Distances, Kernels, and Metric Transforms - Virtual via Bluejeans at 11:00am"}],"uid":"27544","created_gmt":"2021-04-05 12:00:26","changed_gmt":"2021-04-05 12:03:50","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2021-04-06T12:00:00-04:00","event_time_end":"2021-04-06T13:00:00-04:00","event_time_end_last":"2021-04-06T13:00:00-04:00","gmt_time_start":"2021-04-06 16:00:00","gmt_time_end":"2021-04-06 17:00:00","gmt_time_end_last":"2021-04-06 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"645855":{"#nid":"645855","#data":{"type":"event","title":"ARC Seminar: Quanquan C. Liu (MIT)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EARC Seminar \u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EQuanquan C. Liu (MIT)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EWednesday, March 31, 2021\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EVirtual via Bluejeans - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003EParallel Algorithms for Graph Computations\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003EParallel algorithms are often used in practice for their concrete speed-ups compared to standard\u0026nbsp;sequential algorithms in today\u0026#39;s data processing architecture. Algorithms for problems such as triangle counting and k-core decompositions are used in applications such graph visualization, community detection, and graph clustering algorithms. In this talk, I will discuss several novel parallel algorithms for graph computations (in both the static and dynamic settings) that operate in the work-depth (the standard model for shared-memory multicore systems) and the massively parallel computation (MPC) model (the standard for large-scale multi-machine distributed architectures). I will discuss in detail two specific algorithms. In the static setting, I will discuss a O(log log n)-round MPC algorithm that exactly counts the number of triangles and performs in O(n^{\\delta}) (for any constant \\delta) space per machine, and total space O(m \\alpha) where \\alpha is the arboricity of the graph.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIn the dynamic, work-depth setting, I will talk about some very recent work on parallel (2+\\epsilon)-approximate k-core decompositions, a central subroutine in many different types of applications. All discussed algorithms improve upon the theoretical guarantees of previous work. In addition, we implemented all algorithms under experimental settings and found they exhibit improved performances compared to previous implementations on graphs obtained from the Stanford Large Network Dataset Collection (SNAP). I will conclude with some interesting future work.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022http:\/\/quanquancliu.com\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022http:\/\/arc.gatech.edu\/node\/121\u0022\u003Ehttp:\/\/arc.gatech.edu\/node\/121\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Parallel Algorithms for Graph Computations - Virtual via Bluejeans at 11:00am"}],"uid":"27544","created_gmt":"2021-03-29 16:55:11","changed_gmt":"2021-03-29 16:57:00","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2021-03-31T12:00:00-04:00","event_time_end":"2021-03-31T13:00:00-04:00","event_time_end_last":"2021-03-31T13:00:00-04:00","gmt_time_start":"2021-03-31 16:00:00","gmt_time_end":"2021-03-31 17:00:00","gmt_time_end_last":"2021-03-31 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"645680":{"#nid":"645680","#data":{"type":"event","title":"ARC\/ACO Student Seminar: Jingyan Wang (CMU)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EARC\/ACO Student Seminar \u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EJingyan Wang (CMU)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EFriday, April 2, 2021\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align =\u0022center\u0022\u003E\u003Cstrong\u003EVirtual via Bluejeans - 12:00 pm\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp;\u0026nbsp;\u003C\/strong\u003ETowards Understanding and Mitigating Biases\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003EThere are many problems in real life that involve aggregating evaluation from people, such as hiring, peer grading and conference peer review. In this talk, I describe three types of biases that may arise in such problems, and propose methods to mitigate them. (1) We consider miscalibration, that is, different people have different calibration scales. We propose randomized algorithms that provably extract useful information under arbitrary miscalibration. (2) We consider the bias induced by the outcome experienced by people. For example, student ratings in teaching evaluation are affected by the grading leniency of the instructors. We propose an adaptive algorithm that debiases people\u0026#39;s ratings under very mild assumptions of the biases. (3) Estimation bias arises when algorithms yield different performance on different subgroups of the population. We analyze the statistical bias (defined as the expected value of the estimate minus the true value) when using the maximum-likelihood estimator on pairwise comparison data, and then propose a simple modification of the estimator to reduce the bias.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/www.cs.cmu.edu\/~jingyanw\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022http:\/\/arc.gatech.edu\/node\/121\u0022\u003Ehttp:\/\/arc.gatech.edu\/node\/121\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Towards Understanding and Mitigating Biases -Virtual via Bluejeans at 12:00pm"}],"uid":"27544","created_gmt":"2021-03-24 17:44:12","changed_gmt":"2021-03-24 17:44:12","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2021-04-02T13:00:00-04:00","event_time_end":"2021-04-02T14:00:00-04:00","event_time_end_last":"2021-04-02T14:00:00-04:00","gmt_time_start":"2021-04-02 17:00:00","gmt_time_end":"2021-04-02 18:00:00","gmt_time_end_last":"2021-04-02 18:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"645458":{"#nid":"645458","#data":{"type":"event","title":"ARC Colloquium:  Ankur Moitra (MIT)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC) \u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAnkur Moitra (MIT)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, April 5, 2021\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EVirtual via Bluejeans - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003EAlgorithmic Foundations for the Diffraction Limit\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003EFor more than a century and a half it has been widely-believed that the physics of diffraction imposes certain fundamental limits on the resolution of an optical system. However our understanding of what exactly can and cannot be resolved has never risen above heuristic arguments which, even worse, appear contradictory.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIn this work we remedy this gap by studying the diffraction limit as a statistical inverse problem and, based on connections to provable algorithms for learning mixture models, we rigorously prove upper and lower bounds on how many photons we need (and how precisely we need to record their locations) to resolve closely-spaced point sources. Moreover we show the emergence of a phase transition, which helps explain why the diffraction limit can be broken in some domains but not in others.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThis is based on joint work with Sitan Chen.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/math.mit.edu\/directory\/profile.php?pid=1502\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022http:\/\/arc.gatech.edu\/node\/121\u0022\u003Ehttp:\/\/arc.gatech.edu\/node\/121\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Algorithmic Foundations for the Diffraction Limit - Virtual via Bluejeans at 11:00am"}],"uid":"27544","created_gmt":"2021-03-17 14:09:47","changed_gmt":"2021-03-24 15:33:43","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2021-04-05T12:00:00-04:00","event_time_end":"2021-04-05T13:00:00-04:00","event_time_end_last":"2021-04-05T13:00:00-04:00","gmt_time_start":"2021-04-05 16:00:00","gmt_time_end":"2021-04-05 17:00:00","gmt_time_end_last":"2021-04-05 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"645461":{"#nid":"645461","#data":{"type":"event","title":"ARC Colloquium:  Amin Coja-Oghlan (Goethe University, Frankfurt)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC) \u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAmin Coja-Oghlan (Goethe University, Frankfurt)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, April 12, 2021\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EVirtual via Bluejeans - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003EGroup Testing\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003EIn the group testing problem the goal is to identify a small number of infected individuals within a large population by conducting as small a number of tests as possible. The tests are assumed to accept pools of individuals rather than just single individuals, with a test returning a positive result iff at least one individual in the pool is actually infected. Mathematically we ask for information-theoretic lower bounds showing that a certain number of tests is necessary to correctly learn the set of infected individuals as well as algorithmic upper bounds showing that a certain number of tests suffice. In this talk I am going to present some mathematical results, some experimental results and some open problems.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/simons.berkeley.edu\/people\/amin-coja-oghlan\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022http:\/\/arc.gatech.edu\/node\/121\u0022\u003Ehttp:\/\/arc.gatech.edu\/node\/121\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Group Testing - Virtual via Bluejeans at 11:00am"}],"uid":"27544","created_gmt":"2021-03-17 14:36:19","changed_gmt":"2021-03-17 14:36:19","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2021-04-12T12:00:00-04:00","event_time_end":"2021-04-12T13:00:00-04:00","event_time_end_last":"2021-04-12T13:00:00-04:00","gmt_time_start":"2021-04-12 16:00:00","gmt_time_end":"2021-04-12 17:00:00","gmt_time_end_last":"2021-04-12 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"643817":{"#nid":"643817","#data":{"type":"event","title":"ARC Colloquium: Jan Vondrak (Stanford)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC) \u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EJan Vondrak (Stanford)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, March 29, 2021\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EVirtual via Bluejeans - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle: \u003C\/strong\u003ECombinatorial allocation, submodular functions, and Nash social welfare\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003EI will discuss the problem of allocating indivisible goods to agents in order to optimize a certain welfare objective. Various objectives can be considered, the most natural being the summation of valuations of the participating agents. The \u0026quot;Nash social welfare\u0026quot; is an alternative objective which goes back to John Nash\u0026#39;s work in the 1950s; it is the\u0026nbsp;\u003Cem\u003Egeometric average\u003C\/em\u003E\u0026nbsp;rather than a sum of valuations, which has several desirable properties such as balancing total welfare with fairness. On the technical side, it presents a significantly different problem, with connections to areas such as matching theory, computation of the permanent, and stable polynomials.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EOur new result is a constant-factor approximation for Nash social welfare, whenever the valuation functions are submodular.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E(Joint work with Wenzheng Li.)\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/theory.stanford.edu\/~jvondrak\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022http:\/\/arc.gatech.edu\/node\/121\u0022\u003Ehttp:\/\/arc.gatech.edu\/node\/121\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Combinatorial allocation, submodular functions, and Nash social welfare - Virtual via Bluejeans at 11:00am"}],"uid":"27544","created_gmt":"2021-02-03 14:51:49","changed_gmt":"2021-03-15 15:06:20","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2021-03-29T12:00:00-04:00","event_time_end":"2021-03-29T13:00:00-04:00","event_time_end_last":"2021-03-29T13:00:00-04:00","gmt_time_start":"2021-03-29 16:00:00","gmt_time_end":"2021-03-29 17:00:00","gmt_time_end_last":"2021-03-29 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"644451":{"#nid":"644451","#data":{"type":"event","title":"ARC Colloquium: Avrim Blum (TTIC)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC) \u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAvrim Blum\u003C\/strong\u003E \u003Cstrong\u003E (TTIC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, March 22, 2021\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EVirtual via Bluejeans - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle: \u003C\/strong\u003EOn learning in the presence of biased data and strategic behavior\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003EIn this talk I will discuss two lines of work involving learning in the presence of biased data and strategic behavior.\u0026nbsp; In the first, we ask whether fairness constraints on learning algorithms can actually improve the accuracy of the classifier produced, when training data is unrepresentative or corrupted due to bias.\u0026nbsp;\u0026nbsp; Typically, fairness constraints are analyzed as a tradeoff with classical objectives such as accuracy.\u0026nbsp; Our results here show there are natural scenarios where they can be a win-win, helping to improve overall accuracy.\u0026nbsp; In the second line of work we consider strategic classification: settings where the entities being measured and classified wish to be classified as positive (e.g., college admissions) and will try to modify their observable features if possible to make that happen.\u0026nbsp;\u0026nbsp; We consider this in the online setting where a particular challenge is that updates made by the learning algorithm will change how the inputs behave as well.\u0026nbsp;\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/ttic.uchicago.edu\/~avrim\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022http:\/\/arc.gatech.edu\/node\/121\u0022\u003Ehttp:\/\/arc.gatech.edu\/node\/121\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"On learning in the presence of biased data and strategic behavior - Virtual via Bluejeans at 11:00am"}],"uid":"27544","created_gmt":"2021-02-18 18:19:17","changed_gmt":"2021-03-15 14:25:26","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2021-03-22T12:00:00-04:00","event_time_end":"2021-03-22T13:00:00-04:00","event_time_end_last":"2021-03-22T13:00:00-04:00","gmt_time_start":"2021-03-22 16:00:00","gmt_time_end":"2021-03-22 17:00:00","gmt_time_end_last":"2021-03-22 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"642859":{"#nid":"642859","#data":{"type":"event","title":"ARC Colloquium: Rico Zenklusen (ETH Zurich)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC) \u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003ERico Zenklusen (ETH Zurich)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, March 1, 2021\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EVirtual via Bluejeans - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle: \u003C\/strong\u003EBridging the Gap Between Tree and Connectivity Augmentation: Unified and Stronger Approaches\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003EThe Connectivity Augmentation Problem (CAP) is one of the most basic survivable network design problems. It asks about increasing the edge-connectivity of a graph G by one unit through adding a smallest number of additional edges from a given set. If the edge-connectivity of G is odd, it reduces to a heavily studied special case known as the Tree Augmentation Problem (TAP). Despite significant recent progress on TAP, only very recently, Byrka, Grandoni, and Ameli (STOC 2020) managed to obtain an approximation algorithm for CAP with guarantee better than 2 by presenting a 1.91-approximation based on techniques disjoint from recent TAP advances.\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\nIn this talk, I will present new methods that allow for leveraging insights and techniques from TAP to approach CAP. Combined with a novel analysis technique, we obtain a 1.393-approximation for CAP. This significantly improves in a unified way on the previously best approximation factor for CAP (1.91) and also TAP (1.458).\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\nThis is joint work with Federica Cecchetto and Vera Traub.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/math.ethz.ch\/ifor\/people\/rico-zenklusen.html\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022http:\/\/arc.gatech.edu\/node\/121\u0022\u003Ehttp:\/\/arc.gatech.edu\/node\/121\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Bridging the Gap Between Tree and Connectivity Augmentation: Unified and Stronger Approaches -Virtual via Bluejeans at 11:00am"}],"uid":"27544","created_gmt":"2021-01-12 17:36:49","changed_gmt":"2021-02-16 16:16:18","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2021-03-01T11:00:00-05:00","event_time_end":"2021-03-01T12:00:00-05:00","event_time_end_last":"2021-03-01T12:00:00-05:00","gmt_time_start":"2021-03-01 16:00:00","gmt_time_end":"2021-03-01 17:00:00","gmt_time_end_last":"2021-03-01 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"642861":{"#nid":"642861","#data":{"type":"event","title":"ARC Day with keynote by Uriel Feige (Weizmann Institute)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EARC Day \u003C\/strong\u003E\u003Cem\u003Ewith keynote by\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EUriel Feige (Weizmann Institute)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, February 8, 2021\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EVirtual via Bluejeans - 10:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle: \u003C\/strong\u003EFaithful rounding of linear programs\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003EA common paradigm in approximation algorithm is to formulate the NP-hard optimization problem as an integer program, relax it to a linear program, solve the linear program optimally, and then round the fractional solution to an integral solution. An instance of this approach that is relevant to the current talk is the algorithm of Lenstra, Shmoys and Tardos [1990] for scheduling unrelated parallel machines. The rounding technique developed there inspired more recent algorithms for allocation of indivisible items. The context of allocation problems involves fairness considerations that motivate a refined version of the rounding technique, that we refer to as ``faithful rounding\u0026quot;. In this talk we shall explain the faithful rounding technique, survey some of its applications to allocation problems, and discuss challenges that remain in extracting more value out of this rounding technique.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E\u0026nbsp; Born in Jerusalem, Uriel Feige earned his BSc from the Technion, and his MSc and PhD from the Weizmann Institute of Science, both under the guidance of Adi Shamir. After conducting postdoctoral research at Princeton University and at the IBM T.J. Watson Research Center, he joined the Weizmann Institute in 1992. From 2004-2007, he took leave from the Weizmann Institute to work with Microsoft Research\u0026rsquo;s Theory Group, and he continues to serve as a visiting researcher in Microsoft Research, Herzeliya. His main research areas are algorithms, computational complexity, and algorithmic game theory. His work was recognized by some awards, including the 2001 Godel Prize and the 2005 SIAM Outstanding Paper Prize.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022http:\/\/www.wisdom.weizmann.ac.il\/~feige\/\u0022\u003EUriel Feige\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E_________________\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ESwati Gupta (Georgia Tech)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u0026nbsp; Electrical Flows over Spanning Trees\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003EThe network reconfiguration problem seeks to find a rooted tree T such that the energy of the (unique) feasible electrical flow over T is minimized. The tree requirement on the support of the flow is motivated by operational constraints in electricity distribution networks. Existing results on convex optimization over vertices of polytopes and on the structure of electrical flows do not give guarantees for this problem, while many heuristic methods have been developed in the power systems community as early as 1989. Our main contribution is to give the first provable approximation guarantees for the network reconfiguration problem. We provide novel lower bounds and corresponding approximation factors for various settings ranging from min{O(m \u0026minus; n), O(n)} for general graphs, to O(\\sqrt{n}) over grids with uniform resistances on edges, and O(1) for grids with uniform edge resistances and demands. To obtain the result for general graphs, we propose a new method for (approximate) spectral graph sparsification, which may be of independent interest. Using insights from our theoretical results, we propose a general heuristic for the network reconfiguration problem that is orders of magnitude faster than existing methods in the literature, while obtaining comparable performance. This talk is based on joint work with Hassan Mortagy, Ali Khodabakhsh and Evdokia Nikolova.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/swatigupta.tech\/\u0022\u003ESwati Gupta\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E_________________\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAnton Bernshteyn (Georgia Tech)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u0026nbsp; A fast distributed algorithm for $(\\Delta + 1)$-edge-coloring\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003EA celebrated theorem of Vizing says that every graph $G$ of maximum degree $\\Delta$ is $(\\Delta+1)$-edge-colorable. In this talk I will describe a deterministic distributed algorithm in the LOCAL model that finds a $(\\Delta+1)$-edge-coloring in the number of rounds that is polynomial in $\\Delta$ and $\\log n$, where $n = |V(G)|$. This is the first distributed algorithm for $(\\Delta + 1)$-edge-coloring with running time better than $O(\\mathrm{diameter}(G))$.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022http:\/\/people.math.gatech.edu\/~abernshteyn3\/\u0022\u003EAnton Bernshteyn\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E_________________\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022http:\/\/arc.gatech.edu\/node\/121\u0022\u003Ehttp:\/\/arc.gatech.edu\/node\/121\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThe Algorithms \u0026amp; Randomness Center presents ARC DAY with keynote speaker Uriel Feige of the Weizmann Institute, along with talks by Swati Gupta and Anton Bernshteyn of Georgia Tech.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Faithful rounding of linear programs -Virtual via Bluejeans at 10:00am"}],"uid":"27544","created_gmt":"2021-01-12 17:43:36","changed_gmt":"2021-01-27 14:55:55","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2021-02-08T10:00:00-05:00","event_time_end":"2021-02-08T12:10:00-05:00","event_time_end_last":"2021-02-08T12:10:00-05:00","gmt_time_start":"2021-02-08 15:00:00","gmt_time_end":"2021-02-08 17:10:00","gmt_time_end_last":"2021-02-08 17:10:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"641931":{"#nid":"641931","#data":{"type":"event","title":"ARC Colloquium: Zhao Song (Princeton \u0026 Institute for Advanced Study)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC) \u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EZhao Song (Princeton \u0026amp; Institute for Advanced Study)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, November 14, 2020\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EVirtual via Bluejeans - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle: \u003C\/strong\u003EFaster Optimization : From Linear Programming to Deep Learning\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003EMany important real-life problems, in both convex and non-convex settings, can be solved using path-following optimization methods. The running time of optimization algorithms is typically governed\u0026nbsp;by two components -- the number of iterations and the cost-per-iteration. For decades, the vast majority of research effort was dedicated to improving the number of iterations required for convergence. A recent line of work of ours shows that the\u0026nbsp;\u003Cem\u003Ecost-per-iteration\u003C\/em\u003E\u0026nbsp;can be dramatically\u0026nbsp;improved using a careful combination of dynamic data structures with `robust\u0026#39; variants of the optimization method. A central ingredient is the use of randomized linear algebra for dimensionality\u0026nbsp;reduction (e.g.,\u0026nbsp; linear sketching) for fast maintenance of dynamic matrix problems.\u0026nbsp;This framework\u0026nbsp;recently led to many breakthroughs on decade-old optimization problems.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIn this talk, I will present the framework\u0026nbsp;underlying these breakthroughs, focusing on faster\u0026nbsp;algorithms for linear programming and deep learning. We will first present how to use the above\u0026nbsp;idea to speed up general LP solvers by providing an n^omega + n^{2+1\/18} time algorithm.\u0026nbsp;We then show how to apply similar ideas in the *non-convex*\u0026nbsp;setting of deep learning. We provide both a theoretical result of a near-linear training algorithm for (overparametrized) neural networks, and an experimental application of LP techniques to speed up neural network training in practice.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/www.ias.edu\/scholars\/zhao-song\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022http:\/\/arc.gatech.edu\/node\/121\u0022\u003Ehttp:\/\/arc.gatech.edu\/node\/121\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Faster Optimization : From Linear Programming to Deep Learning - Virtual via Bluejeans at 11:00am"}],"uid":"27544","created_gmt":"2020-12-08 13:53:30","changed_gmt":"2020-12-08 13:53:30","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2020-12-14T11:00:00-05:00","event_time_end":"2020-12-14T12:00:00-05:00","event_time_end_last":"2020-12-14T12:00:00-05:00","gmt_time_start":"2020-12-14 16:00:00","gmt_time_end":"2020-12-14 17:00:00","gmt_time_end_last":"2020-12-14 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"641623":{"#nid":"641623","#data":{"type":"event","title":"ARC and Indo-US Virtual Center Seminar: Zongchen Chen (Georgia Tech)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC) and\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EIndo-US Virtual Center Seminar\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EZonchen Chen (Georgia Tech)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, November 30, 2020\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EVirtual via BlueJeans - 11:00am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003EOptimal Mixing of Glauber Dynamics: Entropy Factorization via High-Dimensional Expansion\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003EWe consider the Glauber dynamics (also called Gibbs sampling) for sampling from a discrete high-dimensional space, where in each step\u0026nbsp;one variable is chosen uniformly at random and gets updated conditional on all other variables. We show an optimal mixing time bound for\u0026nbsp;the Glauber dynamics in a variety of settings. Our work presents an improved version of the spectral independence approach of Anari et al.\u0026nbsp;(2020) and shows O(nlogn) mixing time for graphical models\/spin systems on any n-vertex graph of bounded degree when the maximum\u0026nbsp;eigenvalue of an associated influence matrix is bounded. Our proof approach combines classic tools of entropy tensorization\/factorization\u0026nbsp;and recent developments of high-dimensional expanders.\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\nAs an application of our results, for the hard-core model on independent sets weighted by a fugacity lambda, we establish O(nlogn) mixing\u0026nbsp;time for the Glauber dynamics on any n-vertex graph of constant maximum degree D when lambda\u0026lt;lambda_c(D) where lambda_c(D) is\u0026nbsp;the critical point for the uniqueness\/non-uniqueness phase transition on the D-regular tree. More generally, for any antiferromagnetic 2-spin\u0026nbsp;system we prove O(nlogn) mixing time of the Glauber dynamics on any bounded degree graph in the corresponding tree uniqueness\u0026nbsp;region. Our results apply more broadly; for example, we also obtain O(nlogn) mixing for sampling random q-colorings of triangle-free\u0026nbsp;graphs of maximum degree D when the number of colors satisfies q \u0026gt; aD where a = 1.763\u0026hellip;, and O(mlogn) mixing for generating random\u0026nbsp;matchings of any graph with bounded degree and m edges.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/sites.google.com\/view\/zongchenchen\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022http:\/\/arc.gatech.edu\/node\/121\u0022\u003Ehttp:\/\/arc.gatech.edu\/node\/121\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Optimal Mixing of Glauber Dynamics: Entropy Factorization via High-Dimensional Expansion: Virtual via Bluejeans @ 11:00am"}],"uid":"27544","created_gmt":"2020-11-24 14:12:27","changed_gmt":"2020-11-24 14:14:17","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2020-11-30T11:00:00-05:00","event_time_end":"2020-11-30T12:00:00-05:00","event_time_end_last":"2020-11-30T12:00:00-05:00","gmt_time_start":"2020-11-30 16:00:00","gmt_time_end":"2020-11-30 17:00:00","gmt_time_end_last":"2020-11-30 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"639556":{"#nid":"639556","#data":{"type":"event","title":"ARC Colloquium: Surbhi Goel (Univ. of Texas at Austin)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC) \u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003ESurbhi Goel (Univ. of Texas at Austin)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, November 9, 2020\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EVirtual via Bluejeans - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle: \u003C\/strong\u003EComputational Complexity of Learning Neural Networks over Gaussian Marginals\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003EA major challenge in the theory of deep learning is to understand the computational complexity of learning basic families of neural networks (NNs). The challenge here arises from the non-convexity of the associated optimization problem. It is well known that the learning problem is computationally intractable in the worst case. Positive results have circumvented this hardness by making assumptions on the distribution as well as the label noise.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIn this talk, we focus on the problem of learning shallow NNs under the benign gaussian input distribution. We first show a super-polynomial Statistical Query (SQ) lower bound in the noiseless setting. We further show how to use this result to obtain a super-polynomial SQ lower bound for learning a single neuron in the agnostic noise model. Lastly, on the positive side, we describe a gradient-based algorithm for approximately learning ReLUs which runs in polynomial time.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThis talk is based on multiple works with Ilias Diakonikolas, Aravind Gollakota, Zhihan Jin, Sushrut Karmalkar, Adam Klivans and Mahdi Soltanolkotabi\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/www.cs.utexas.edu\/~surbhi\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022http:\/\/arc.gatech.edu\/node\/121\u0022\u003Ehttp:\/\/arc.gatech.edu\/node\/121\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Computational Complexity of Learning Neural Networks over Gaussian Marginals: Virtual via Bluejeans at 11:00am"}],"uid":"27544","created_gmt":"2020-09-25 14:24:21","changed_gmt":"2020-11-02 16:25:28","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2020-11-09T11:00:00-05:00","event_time_end":"2020-11-09T12:00:00-05:00","event_time_end_last":"2020-11-09T12:00:00-05:00","gmt_time_start":"2020-11-09 16:00:00","gmt_time_end":"2020-11-09 17:00:00","gmt_time_end_last":"2020-11-09 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"638670":{"#nid":"638670","#data":{"type":"event","title":"ThinkTankTalk:  B. Aditya Prakash (Georgia Tech)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC) \u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EThinkTankTalk\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EB. Aditya Prakash (Georgia Tech)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, November 16, 2020\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EVirtual via Bluejeans - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle: \u003C\/strong\u003ENetworks and Propagation for Fun, Profit and Social Good\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003EGiven a population network and current infection data of a contagious disease like flu, how to effectively allocate vaccines? What if the infection patterns change? How to fill-in missing infections, automatically?\u0026nbsp;Can we guess if a\u0026nbsp;user is sick from her tweet? Answering all these questions involves the study of aggregated \u0026lsquo;propagation (cascade)\u0026rsquo;-based dynamics over complex connectivity patterns.\u0026nbsp;As diverse as these problems sound, they can all be\u0026nbsp;approached using modern tools of network science and dynamics. Networks are powerful tools for modeling processes and situations of interest in real-life. They are ubiquitous, from online social networks, gene-regulatory\u0026nbsp;networks, to router graphs. Dynamical processes on networks are also widespread across several domains. Understanding such propagation processes will eventually enable us to manipulate them for our benefit e.g.,\u0026nbsp;understanding dynamics of epidemic spreading over graphs helps design more robust policies for immunization.\u0026nbsp;\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\nIn this talk we will focus on leveraging propagation-style processes on large networks to understand, predict and manage behaviors. We will focus\u0026nbsp;largely on public health applications and present some of our past and ongoing work on theoretical results on behavior of fundamental models and scalable algorithms for various associated tasks e.g. immunizing, detecting and reverse engineering epidemics.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/www.cc.gatech.edu\/~badityap\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022http:\/\/arc.gatech.edu\/node\/121\u0022\u003Ehttp:\/\/arc.gatech.edu\/node\/121\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Networks and Propagation for Fun, Profit and Social Good: Virtual via Bluejeans at 11:00am"}],"uid":"27544","created_gmt":"2020-09-01 17:52:10","changed_gmt":"2020-11-02 16:02:32","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2020-11-16T11:00:00-05:00","event_time_end":"2020-11-16T12:00:00-05:00","event_time_end_last":"2020-11-16T12:00:00-05:00","gmt_time_start":"2020-11-16 16:00:00","gmt_time_end":"2020-11-16 17:00:00","gmt_time_end_last":"2020-11-16 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"637733":{"#nid":"637733","#data":{"type":"event","title":"ARC Colloquium: Matthew Fahrbach (Google Research)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC) \u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMatthew Fahrbach\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, November 2, 2020\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EVirtual via Bluejeans - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle: \u003C\/strong\u003EEdge-Weighted Online Bipartite Matching\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003EOnline bipartite matching is one of the most fundamental problems in the online algorithms literature. Karp, Vazirani, and Vazirani (STOC 1990) introduced an elegant algorithm for the unweighted bipartite matching that achieves an optimal competitive ratio of 1-1\/e. Aggarwal et al. (SODA 2011) later generalized their algorithm and analysis to the vertex-weighted case. Little is known, however, about the most general edge-weighted problem aside from the trivial 1\/2-competitive greedy algorithm. In this paper, we present the first online algorithm that breaks the long-standing 1\/2 barrier and achieves a competitive ratio of at least 0.5086. In light of the hardness result of Kapralov, Post, and Vondr\u0026aacute;k (SODA 2013) that restricts beating a 1\/2 competitive ratio for the more general problem of monotone submodular welfare maximization, our result can be seen as strong evidence that edge-weighted bipartite matching is strictly easier than submodular welfare maximization in the online setting.\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\nThe main ingredient in our online matching algorithm is a novel subroutine called online correlated selection (OCS), which takes a sequence of pairs of vertices as input and selects one vertex from each pair. Instead of using a fresh random bit to choose a vertex from each pair, the OCS negatively correlates decisions across different pairs and provides a quantitative measure on the level of correlation. We believe our OCS technique is of independent interest and will find further applications in other online optimization problems.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/www.matthewfahrbach.com\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022http:\/\/arc.gatech.edu\/node\/121\u0022\u003Ehttp:\/\/arc.gatech.edu\/node\/121\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Edge-Weighted Online Bipartite Matching: Virtual via Bluejeans at 11:00am"}],"uid":"27544","created_gmt":"2020-08-10 16:03:27","changed_gmt":"2020-10-27 12:12:04","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2020-11-02T11:00:00-05:00","event_time_end":"2020-11-02T12:00:00-05:00","event_time_end_last":"2020-11-02T12:00:00-05:00","gmt_time_start":"2020-11-02 16:00:00","gmt_time_end":"2020-11-02 17:00:00","gmt_time_end_last":"2020-11-02 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"637464":{"#nid":"637464","#data":{"type":"event","title":"ARC Colloquium: Nick Harvey (Univ. of British Columbia, Vancouver) ","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC) \u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003ENick Harvey (Univ. of British Columbia, Vancouver)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, October 26, 2020\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EVirtual via Bluejeans - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle: \u003C\/strong\u003EOptimal anytime regret with two experts\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003EA central problem in online learning is regret minimization in the expert setting. The famous multiplicative weights method achieves the optimal regret asymptotically if the number of experts is large, and the time horizon is known in advance. Optimal algorithms are also known if there are exactly two, three or four experts, and the time horizon is known in advance.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIn the \u0026ldquo;anytime\u0026rdquo; setting, where the time horizon is not known in advance, algorithms can be obtained by the \u0026ldquo;doubling trick\u0026rdquo;, but they are not optimal, let alone practical. No minimax optimal algorithm was previously known in the anytime setting, regardless of the number of experts. We design the first minimax optimal algorithm for minimizing regret in the anytime setting. We consider the case of two experts, and prove that the optimal regret is \\gamma \\sqrt{t}\/2 at all time steps t, where \\gamma is a natural constant that arose 35 years ago in studying fundamental properties of Brownian motion. The algorithm is designed by considering a continuous analogue of the regret problem, which is solved using ideas from stochastic calculus.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/www.cs.ubc.ca\/~nickhar\/\u0022\u003ESpeaker\u0026#39;s Webpage \u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Cem\u003E\u003Ca href=\u0022http:\/\/arc.gatech.edu\/node\/121\u0022\u003Ehttp:\/\/arc.gatech.edu\/node\/121\u003C\/a\u003E\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Optimal anytime regret with two experts: Virtual via Bluejeans at 11:00am"}],"uid":"27544","created_gmt":"2020-08-03 16:52:37","changed_gmt":"2020-10-20 13:13:11","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2020-10-26T12:00:00-04:00","event_time_end":"2020-10-26T13:00:00-04:00","event_time_end_last":"2020-10-26T13:00:00-04:00","gmt_time_start":"2020-10-26 16:00:00","gmt_time_end":"2020-10-26 17:00:00","gmt_time_end_last":"2020-10-26 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"638750":{"#nid":"638750","#data":{"type":"event","title":"ARC Colloquium: Sumegha Garg (Princeton)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003ESumegha Garg (Princeton)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, October 12, 2020\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EVirtual via Bluejeans - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003E\u0026nbsp;\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003EExtractor-based Approach to Proving Memory-Sample Lower Bounds for Learning\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003EA recent line of work has focused on the following question: Can one prove strong unconditional lower bounds on the number of samples needed for learning under memory constraints? We study an extractor-based approach to proving such bounds for a large class of learning problems as follows.\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\nA matrix M: A x X -\u0026gt; {-1,1} corresponds to the following learning problem: An unknown function f in X is chosen uniformly at random. A learner tries to learn f from a stream of samples, (a_1, b_1), (a_2, b_2) ..., where for every i, a_i in A is chosen uniformly at random and b_i = M(a_i,f).\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\nAssume that k, l, r are such that any submatrix of M, with at least 2^{-k}|A| rows and at least 2^{-l}|X| columns, has a bias of at most 2^{-r} (extractor property). We show that any learning algorithm for the learning problem corresponding to M requires either a memory of size at least \u0026Omega;(k l), or at least 2^{\u0026Omega;(r)} samples.\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\nWe also extend the lower bounds to a learner that is allowed two passes over the stream of samples. In particular, we show that any two-pass algorithm for learning parities of size n requires either a memory of size \u0026Omega;(n^{3\/2}) or at least 2^{\u0026Omega;(n^{1\/2})} samples.\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\nJoint works with Ran Raz and Avishay Tal.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003E----------------------------------\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003E\u003Ca href=\u0022https:\/\/www.cs.princeton.edu\/~sumeghag\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022http:\/\/arc.gatech.edu\/node\/121\u0022\u003Ehttp:\/\/arc.gatech.edu\/node\/121\u003C\/a\u003E\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/strong\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Extractor-based Approach to Proving Memory-Sample Lower Bounds for Learning: Virtual via Bluejeans at 11:00am"}],"uid":"27544","created_gmt":"2020-09-03 14:56:21","changed_gmt":"2020-09-29 16:23:41","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2020-10-12T12:00:00-04:00","event_time_end":"2020-10-12T13:00:00-04:00","event_time_end_last":"2020-10-12T13:00:00-04:00","gmt_time_start":"2020-10-12 16:00:00","gmt_time_end":"2020-10-12 17:00:00","gmt_time_end_last":"2020-10-12 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"638663":{"#nid":"638663","#data":{"type":"event","title":"ThinkTankTalk:  Daniel Molzahn (Georgia Tech)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC) \u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EThinkTankTalk\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EDaniel\u0026nbsp;Molzahn (Georgia Tech)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, October 5, 2020\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EVirtual via Bluejeans - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle: \u003C\/strong\u003EApplications of Polynomial Optimization in Electric Power Systems\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003EElectric power systems are critical infrastructure that underlie almost all aspects of modern society. With rapidly increasing quantities of renewable generation and the continuing expansion of electricity markets, electric power systems are undergoing significant changes. New algorithms for optimizing the design and operation of electric power systems are needed in order to enable these transformational changes.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThe so-called \u0026ldquo;power flow equations\u0026rdquo; are at the heart of power system optimization problems. These equations, which model the physics of electric power grids, can be represented as systems of polynomials. This presentation describes recent work and open questions in applying polynomial optimization theory to power system optimization problems. Some open questions involve developing efficient methods for computing multiple real solutions to the power flow equations for given choices of parameters (load demands and generator outputs). When these parameters are allowed to vary, the Lasserre hierarchy of moment\/sum-of-squares relaxations can be applied to compute the global optima of optimization problems constrained by the power flow equations. Relevant questions include deriving sufficient conditions which ensure tightness of these relaxations and developing efficient methods for scaling these relaxations to large systems.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/molzahn.github.io\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022http:\/\/arc.gatech.edu\/node\/121\u0022\u003Ehttp:\/\/arc.gatech.edu\/node\/121\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Applications of Polynomial Optimization in Electric Power Systems: Virtual via Bluejeans at 11:00am"}],"uid":"27544","created_gmt":"2020-09-01 13:24:11","changed_gmt":"2020-09-28 13:04:55","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2020-10-05T12:00:00-04:00","event_time_end":"2020-10-05T13:00:00-04:00","event_time_end_last":"2020-10-05T13:00:00-04:00","gmt_time_start":"2020-10-05 16:00:00","gmt_time_end":"2020-10-05 17:00:00","gmt_time_end_last":"2020-10-05 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"637712":{"#nid":"637712","#data":{"type":"event","title":"ARC Colloquium: Alberto Del Pia (WISC)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC) \u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlberto Del Pia (WISC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, October 19, 2020\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EVirtual via Bluejeans - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle: \u003C\/strong\u003EShort simplex paths in lattice polytopes\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003EIn this talk we discuss the problem of designing a simplex algorithm for linear programs on lattice polytopes that traces \u0026lsquo;short\u0026rsquo; simplex paths from any given vertex to an optimal one. We consider a lattice polytope P contained in [0, k]^n and defined via m linear inequalities. Our first contribution is a simplex algorithm that reaches an optimal vertex by tracing a path along the edges of P of length in O(n^4 k log(nk)). The length of this path is independent on m and it is the best possible up to a polynomial function. In fact, it is only polynomially far from the worst-case diameter, which roughly grows as a linear function in n and k.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EMotivated by the fact that most known lattice polytopes are defined via 0,\u0026plusmn;1 constraint matrices, our second contribution is an iterative algorithm which exploits the largest absolute value \u0026alpha; of the entries in the constraint matrix. We show that the length of the simplex path generated by the iterative algorithm is in O(n^2 k log(nk\u0026alpha;)). In particular, if \u0026alpha; is bounded by a polynomial in n, k, then the length of the simplex path is in O(n^2 k log(nk)).\u003C\/p\u003E\r\n\r\n\u003Cp\u003EFor both algorithms, the number of arithmetic operations needed to compute the next vertex in the path is polynomial in n, m and log k. If k is polynomially bounded by n and m, the algorithm runs in strongly polynomial time.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/wid.wisc.edu\/people\/alberto-del-pia\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022http:\/\/arc.gatech.edu\/node\/121\u0022\u003Ehttp:\/\/arc.gatech.edu\/node\/121\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Short simplex paths in lattice polytopes: Virtual via Bluejeans at 11:00am"}],"uid":"27544","created_gmt":"2020-08-10 13:46:07","changed_gmt":"2020-08-26 13:52:53","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2020-10-19T12:00:00-04:00","event_time_end":"2020-10-19T13:00:00-04:00","event_time_end_last":"2020-10-19T13:00:00-04:00","gmt_time_start":"2020-10-19 16:00:00","gmt_time_end":"2020-10-19 17:00:00","gmt_time_end_last":"2020-10-19 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"637736":{"#nid":"637736","#data":{"type":"event","title":"ARC Colloquium: Richard Peng (Georgia Tech)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC) \u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003ERichard Peng (Georgia Tech)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, August 31, 2020\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EVirtual via Bluejeans - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle: \u003C\/strong\u003ESolving Sparse Linear Systems Faster than Matrix Multiplication\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003ECan linear systems be solved faster than matrix multiplication? While there has been remarkable progress for the special cases of graph structured linear systems, in the general setting, the bit complexity of solving an n-by-n linear system Ax=b is n^\\omega, where \\omega\u0026lt;2.372864 is the matrix multiplication exponent. Improving on this has been an open problem even for sparse linear systems with poly(n) condition number.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EWe present an algorithm that solves linear systems in sparse matrices asymptotically faster than matrix multiplication for any \\omega\u0026gt;2. This speedup holds for any input matrix A with o(n^{\\omega -1}\/\\log(\\kappa(A))) non-zeros, where \\kappa(A) is the condition number of A. For poly(n)-conditioned matrices with O(n) nonzeros, and the current value of \\omega, the bit complexity of our algorithm to solve to within any 1\/poly(n) error is O(n^{2.331645}).\u003C\/p\u003E\r\n\r\n\u003Cp\u003EOur algorithm can be viewed as an efficient, randomized implementation of the block Krylov method via recursive low displacement rank factorizations. It is inspired by the algorithm of [Eberly et al. ISSAC `06 `07] for inverting matrices over finite fields. In our analysis of numerical stability, we develop matrix anti-concentration techniques to bound the smallest eigenvalue and the smallest gap in eigenvalues of semi-random matrices.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EJoint work with Santosh Vempala, manuscript at \u003Ca href=\u0022https:\/\/arxiv.org\/abs\/2007.10254\u0022\u003Ehttps:\/\/arxiv.org\/abs\/2007.10254\u003C\/a\u003E.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/www.cc.gatech.edu\/~rpeng\/index.html\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022http:\/\/arc.gatech.edu\/node\/121\u0022\u003Ehttp:\/\/arc.gatech.edu\/node\/121\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Solving Sparse Linear Systems Faster than Matrix Multiplication: Virtual via Bluejeans at 11:00am"}],"uid":"27544","created_gmt":"2020-08-10 16:11:58","changed_gmt":"2020-08-25 19:02:44","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2020-08-31T12:00:00-04:00","event_time_end":"2020-08-31T13:00:00-04:00","event_time_end_last":"2020-08-31T13:00:00-04:00","gmt_time_start":"2020-08-31 16:00:00","gmt_time_end":"2020-08-31 17:00:00","gmt_time_end_last":"2020-08-31 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"637462":{"#nid":"637462","#data":{"type":"event","title":"ARC Colloquium: Vera Traub (ETH Zurich) ","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC) \u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EVera Traub (ETH Zurich)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, September 28, 2020\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EVirtual via Bluejeans - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle: \u003C\/strong\u003EReducing Path TSP to TSP\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003EIn this talk we present a black-box reduction from the path version of the Traveling Salesman Problem (Path TSP) to the classical tour version (TSP). More precisely, we show that given an \u0026alpha;-approximation algorithm for TSP, then, for any \u03f5\u0026gt;0, there is an (\u0026alpha;+\u03f5)-approximation algorithm for the more general Path TSP. This reduction implies that the approximability of Path TSP is the same as for TSP, up to an arbitrarily small error. This avoids future discrepancies between the best known approximation factors achievable for these two problems, as they have existed until very recently.\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\nTo obtain our result we use a novel way to set up a recursive dynamic program to guess significant parts of an optimal solution. At the core of our dynamic program we deal with instances of a new generalization of (Path) TSP which combines parity constraints with certain connectivity requirements. This problem, which we call \u0026Phi;-TSP, has a constant-factor approximation algorithm and can be reduced to TSP in certain cases when the dynamic program would not make sufficient progress.\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\nThis is joint work with Jens Vygen and Rico Zenklusen.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/math.ethz.ch\/ifor\/people.html?u=vtraub\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Reducing Path TSP to TSP: Virtual via Bluejeans at 11:00am"}],"uid":"27544","created_gmt":"2020-08-03 16:40:05","changed_gmt":"2020-08-14 18:04:06","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2020-09-28T12:00:00-04:00","event_time_end":"2020-09-28T13:00:00-04:00","event_time_end_last":"2020-09-28T13:00:00-04:00","gmt_time_start":"2020-09-28 16:00:00","gmt_time_end":"2020-09-28 17:00:00","gmt_time_end_last":"2020-09-28 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"637417":{"#nid":"637417","#data":{"type":"event","title":"ARC Colloquium: Debmalya Panigrahy (Duke University) ","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC) \u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EDebmalya Panigrahy (Duke University)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, August 24, 2020\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EVirtual via Bluejeans - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle: \u003C\/strong\u003EDeterministic Min-cut in Poly-logarithmic Max-flows\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003EThe min-cut problem in undirected graphs asks for a minimum (weight) subset of edges whose removal disconnects the graph. In the 1990s, Karger developed several randomized (Monte Carlo) algorithms for this problem, leading to an eventual running time bound of \\tilde{O}(m). At the time, the best deterministic algorithms for the problem, from the early 1990s, were much slower and ran in \\tilde{O}(mn) time. This led him to ask whether the min-cut problem can be solved in \\tilde{O}(m) time deterministically as well. Unfortunately, even after almost 30 years, the \\tilde{O}(mn) bound is still the best known for general weighted graphs. In this talk, I will present a new deterministic min-cut algorithm that uses polylog(n) max-flow computations. Using the current best max-flow algorithms, this results in an overall running time of \\tilde{O}(m \\min(\\sqrt{m}, n^{2\/3}}) for weighted graphs, and \\tilde{O}(m^{4\/3}) for unweighted (multi)-graphs, thereby breaking the longstanding \\tilde{O}(mn) bound. (The \\tilde{O} notation hides sub-polynomial factors.) This is based on joint work with Jason Li.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/users.cs.duke.edu\/~debmalya\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003Ca href=\u0022http:\/\/arc.gatech.edu\/node\/121\u0022\u003Ehttp:\/\/arc.gatech.edu\/node\/121\u003C\/a\u003E\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Deterministic Min-cut in Poly-logarithmic Max-flows: Virtual via Bluejeans at 11:00am"}],"uid":"27544","created_gmt":"2020-07-31 14:53:21","changed_gmt":"2020-08-13 19:27:07","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2020-08-24T12:00:00-04:00","event_time_end":"2020-08-24T13:00:00-04:00","event_time_end_last":"2020-08-24T13:00:00-04:00","gmt_time_start":"2020-08-24 16:00:00","gmt_time_end":"2020-08-24 17:00:00","gmt_time_end_last":"2020-08-24 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"637709":{"#nid":"637709","#data":{"type":"event","title":"ARC and Indo-US Virtual Center Seminar: Tselil Schramm (Stanford)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC) \u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003Eand Indo-US Virtual Center Seminar\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003ETselil Schramm (Stanford)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, August 17, 2020\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EVirtual via Bluejeans - 11:30 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003EReconciling Statistical Queries and the Low Degree Likelihood Ratio\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003EIn many high-dimensional statistics problems, we observe information-computation tradeoffs: given access to more data, statistical estimation and inference tasks require fewer computational resources. Though this phenomenon is ubiquitous, we lack rigorous evidence that it is inherent. In the current day, to prove that a statistical estimation task is computationally intractable, researchers must prove lower bounds against each type of algorithm, one by one, resulting in a \u0026quot;proliferation of lower bounds\u0026quot;. We scientists dream of a more general theory which unifies these lower bounds and explains computational intractability in an algorithm-independent way.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIn this talk, I will make one small step towards realizing this dream. I will demonstrate general conditions under which two popular frameworks yield the same information-computation tradeoffs for high-dimensional hypothesis testing: the first being statistical queries in the \u0026quot;SDA\u0026quot; framework, and the second being hypothesis testing with low-degree hypothesis tests, also known as the low-degree-likelihood ratio.\u0026nbsp;Our equivalence theorems capture numerous well-studied high-dimensional learning problems: sparse PCA, tensor PCA, community detection, planted clique, and more.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EBased on joint work with Matthew Brennan, Guy Bresler, Samuel B. Hopkins and Jerry Li.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/tselilschramm.org\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022http:\/\/arc.gatech.edu\/node\/121\u0022\u003Ehttp:\/\/arc.gatech.edu\/node\/121\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Reconciling Statistical Queries and the Low Degree Likelihood Ratio - Virtual via Bluejeans at 11:30am"}],"uid":"27544","created_gmt":"2020-08-10 13:09:48","changed_gmt":"2020-08-10 13:48:34","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2020-08-17T12:30:00-04:00","event_time_end":"2020-08-17T13:30:00-04:00","event_time_end_last":"2020-08-17T13:30:00-04:00","gmt_time_start":"2020-08-17 16:30:00","gmt_time_end":"2020-08-17 17:30:00","gmt_time_end_last":"2020-08-17 17:30:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"637131":{"#nid":"637131","#data":{"type":"event","title":"ARC and Indo-US Virtual Center Seminar: Shayan Oveis Gharan (Univ. of Washington)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC) and Indo-US Virtual Center Seminar\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EShayan Oveis Gharan (University of Washington)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, July 27, 2020\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EVirtual via Bluejeans - 11:30 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003EA (slightly) Improved Approximation algorithm for Metric TSP\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003EI will sketch some of the ideas in our recent 3\/2-eps approximation algorithm for Metric TSP. The field of geometry of polynomials plays a fundamental role in our proof as we use and prove several (new) properties of strongly Rayleigh distributions.\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\nBased on a joint work with Anna Karlin and Nathan Klein\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/homes.cs.washington.edu\/~shayan\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"A (slightly) Improved Approximation algorithm for Metric TSP - Virtual via Bluejeans at 11:30am"}],"uid":"27544","created_gmt":"2020-07-21 17:43:18","changed_gmt":"2020-07-21 17:44:19","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2020-07-27T12:30:00-04:00","event_time_end":"2020-07-27T14:00:00-04:00","event_time_end_last":"2020-07-27T14:00:00-04:00","gmt_time_start":"2020-07-27 16:30:00","gmt_time_end":"2020-07-27 18:00:00","gmt_time_end_last":"2020-07-27 18:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"636929":{"#nid":"636929","#data":{"type":"event","title":"ARC and Indo-US Virtual Center Seminar: Lap Chi Lau (University of Waterloo)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC) and Indo-US Virtual Center Seminar\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003ELap Chi Lau (University of Waterloo)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, July 20, 2020\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EVirtual via Bluejeans - 11:30 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003EA Spectral Approach to Network Design\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003EWe present a spectral approach to design approximation algorithms for network design problems.\u0026nbsp;\u0026nbsp;We observe that the underlying mathematical questions are the spectral rounding problems,\u0026nbsp;which were studied in spectral sparsification and in discrepancy theory.\u0026nbsp;\u0026nbsp;We extend these results to incorporate additional non-negative linear constraints, and show that they can be used to significantly extend the scope of network design problems that can be solved.\u0026nbsp;\u0026nbsp;Our algorithm for spectral rounding is an iterative randomized rounding algorithm based on the regret minimization framework.\u0026nbsp;\u0026nbsp;We may\u0026nbsp;also discuss other applications of the spectral rounding results, including weighted experimental design and additive spectral sparsification.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/cs.uwaterloo.ca\/~lapchi\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"A Spectral Approach to Network Design - Virtual via Bluejeans at 11:30am"}],"uid":"27544","created_gmt":"2020-07-14 13:33:19","changed_gmt":"2020-07-14 13:33:19","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2020-07-20T12:30:00-04:00","event_time_end":"2020-07-20T13:30:00-04:00","event_time_end_last":"2020-07-20T13:30:00-04:00","gmt_time_start":"2020-07-20 16:30:00","gmt_time_end":"2020-07-20 17:30:00","gmt_time_end_last":"2020-07-20 17:30:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"636157":{"#nid":"636157","#data":{"type":"event","title":"ARC Colloquium: Yuanzhi Li (CMU)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC) \u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EYuanzhi Li (CMU)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, June 29, 2020\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EVirtual via Bluejeans - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003EBackward Feature Correction: How can Deep Learning perform Deep Learning\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003EHow does a 110-layer ResNet learn a high-complexity classifier using relatively few training examples and short training time? We present a theory towards explaining this\u0026nbsp;\u003Cstrong\u003Edeep\u003C\/strong\u003E\u0026nbsp;learning\u0026nbsp;process in terms of hierarchical learning. We refer to hierarchical learning as the learner learns to represent a complicated target function by decomposing it into a sequence of simpler functions, to reduce sample and time complexity. This work formally analyzes how multi-layer neural networks can perform such hierarchical learning efficiently and automatically simply by applying stochastic gradient descent (SGD) to the training objective.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EMoreover, we present, to the best of our knowledge, the first theory result indicating how very deep neural networks can be sample and time efficient on certain hierarchical learning tasks, even when no known non-hierarchical algorithms (such as kernel method, linear regression over feature mappings, tensor decomposition, sparse coding, and their simple combinations) are efficient. We establish \u003Cstrong\u003Ea new principle called \u0026ldquo;backward feature correction\u0026rdquo; to show how the features in the lower-level layers in the network can also be improved via\u0026nbsp;training\u0026nbsp;higher-level layers\u003C\/strong\u003E, which we believe is the key to understand the deep learning process in multi-layer neural networks.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EBrief Bio: Yuanzhi Li is an assistant professor at CMU, Machine Learning Department. He did his Ph.D. at Princeton, under the advice of Sanjeev Arora (2014-2018) as well as a one-year postdoc at Stanford. His wife is Yandi Jin.\u0026nbsp;\u0026nbsp;\u003Cbr \/\u003E\r\n----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/www.andrew.cmu.edu\/user\/yuanzhil\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Backward Feature Correction: How can Deep Learning perform Deep Learning - Virtual via Bluejeans at 11:00 am"}],"uid":"27544","created_gmt":"2020-06-11 13:06:40","changed_gmt":"2020-06-24 19:31:51","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2020-06-29T12:00:00-04:00","event_time_end":"2020-06-29T13:00:00-04:00","event_time_end_last":"2020-06-29T13:00:00-04:00","gmt_time_start":"2020-06-29 16:00:00","gmt_time_end":"2020-06-29 17:00:00","gmt_time_end_last":"2020-06-29 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"635860":{"#nid":"635860","#data":{"type":"event","title":"ARC and Indo-US Virtual Center Seminar: Pravesh Kothari (CMU)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC) and Indo-US Virtual Center Seminar\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EPravesh Kothari (CMU)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, June 8, 2020\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EVirtual via Bluejeans - 11:30 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003EOutlier-robust Clustering of Gaussian Mixtures\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003EWe give efficient algorithms for robustly clustering of mixtures of \u0026quot;reasonable\u0026quot; distributions, including the well-known open problem of robustly clustering a mixture of arbitrary Gaussians. Specifically, we\u0026nbsp;give an outlier-robust efficient algorithm for clustering a mixture of k Gaussians with pairwise TV distance 1-exp(k^k\/\\eta). The running time of our algorithm is d^{(k\/\\eta)^{O(k)}}. More generally, our algorithm succeeds for mixtures of distributions that satisfy two well-studied analytic assumptions - certifiable hypercontractivity and anti-concentration. Thus, it extends to clustering mixtures of arbitrary affine transforms of the uniform distribution on the d-dimensional unit sphere. Even the information-theoretic clusterability of distributions satisfying our analytic assumptions was not known and is likely to be of independent interest. Our techniques expand the sum-of-squares toolkit to show robust certifiability of TV-separated Gaussian clusters in data. This involves a low-degree sum-of-squares proof of statements that relate parameter distance to total variation distance simply relying on hypercontractivity and anti-concentration.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIt remains open to improve the running time of the algorithms and to give a robust parameter estimation algorithm for Gaussian mixtures with no separation assumptions.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EBased on joint work with Ainesh Bakshi (CMU).\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/www.cs.princeton.edu\/~kothari\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Outlier-robust Clustering of Gaussian Mixtures - Virtual via Bluejeans at 11:30am"}],"uid":"27544","created_gmt":"2020-06-01 16:07:20","changed_gmt":"2020-06-01 16:09:23","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2020-06-08T12:30:00-04:00","event_time_end":"2020-06-08T13:30:00-04:00","event_time_end_last":"2020-06-08T13:30:00-04:00","gmt_time_start":"2020-06-08 16:30:00","gmt_time_end":"2020-06-08 17:30:00","gmt_time_end_last":"2020-06-08 17:30:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"634657":{"#nid":"634657","#data":{"type":"event","title":"ARC and Indo-US Virtual Center Seminar: Prasad Raghavendra (UC Berkeley)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC) and Indo-US Virtual Center Seminar\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EPrasad Raghavendra (UC Berkeley)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, April 27, 2020\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EVirtual via Bluejeans - 11:30 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003EList-Decodable Learning via Sum of Squares\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003EIn the list-decodable learning setup, an overwhelming majority (say a $1-\\beta$-fraction) of the input data consists of outliers and the goal of an algorithm is to output a small list $\\mathcal{L}$ of hypotheses such that one of them agrees with inliers. \u0026nbsp; We devise list decodable learning algorithms for the problem of linear regression and subspace recovery using the sum of squares SDP hierarchy.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;1)\u0026nbsp; In the list-decodable linear regression problem, we are given labelled examples $\\{(X_i,y_i)\\}_{i \\in [N]}$ containing a subset $S$ of $\\beta N$ {\\it inliers} $\\{X_i \\}_{i \\in S}$ that are drawn i.i.d. from standard Gaussian distribution $N(0,I)$ in $\\mathbb{R}^d$, where the corresponding labels $y_i$ are well-approximated by a linear function $\\hat{\\ell}$. \u0026nbsp;\u003Cbr \/\u003E\r\n\u0026nbsp;\u003Cbr \/\u003E\r\n\u0026nbsp;We devise an algorithm that outputs a list $\\mathcal{L}$ of linear functions such that there exists some $\\ell \\in \\mathcal{L}$ that is close to $\\hat{\\ell}$.\u0026nbsp;\u0026nbsp;\u0026nbsp; \u0026nbsp;This yields the first algorithm for linear regression in a list-decodable setting.\u0026nbsp; Our results hold for a general distribution of examples whose concentration and anti-concentration properties can be certified by low degree sum-of-squares proofs.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;2) In the subspace recovery problem,\u0026nbsp; given a dataset where an $\\alpha$ fraction (less than half) of the data is distributed uniformly in an unknown $k$ dimensional subspace in $d$ dimensions, and with no additional assumptions on the remaining data, the goal is to recover a succinct list of $O(\\frac{1}{\\alpha})$ subspaces one of which is close to the original subspace.\u0026nbsp; We provide the first polynomial time algorithm for the \u0026#39;list decodable subspace recovery\u0026#39; problem.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EJoint work with Morris Yau.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/people.eecs.berkeley.edu\/~prasad\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"List-Decodable Learning via Sum of Squares - Virtual via Bluejeans at 11:30am"}],"uid":"27544","created_gmt":"2020-04-22 19:47:53","changed_gmt":"2020-04-22 20:10:40","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2020-04-27T12:30:00-04:00","event_time_end":"2020-04-27T13:30:00-04:00","event_time_end_last":"2020-04-27T13:30:00-04:00","gmt_time_start":"2020-04-27 16:30:00","gmt_time_end":"2020-04-27 17:30:00","gmt_time_end_last":"2020-04-27 17:30:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"631696":{"#nid":"631696","#data":{"type":"event","title":"\u0022POSTPONED\u0022  ARC Colloquium: Mark A. Davenport (Georgia Tech)","body":[{"value":"\u003Cp align =\u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align =\u0022center\u0022\u003E\u003Cstrong\u003EMark A. Davenport (Georgia Tech)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = center\u003E\u003Cstrong\u003EMonday, March 30, 2020\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = center\u003E\u003Cstrong\u003EKlaus 1116 East - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003ETBA\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003ETBA\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mdav.ece.gatech.edu\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Title TBA - Klaus 1116 East at 11am"}],"uid":"27544","created_gmt":"2020-01-27 14:58:26","changed_gmt":"2020-03-20 11:58:11","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2020-03-30T12:00:00-04:00","event_time_end":"2020-03-30T13:00:00-04:00","event_time_end_last":"2020-03-30T13:00:00-04:00","gmt_time_start":"2020-03-30 16:00:00","gmt_time_end":"2020-03-30 17:00:00","gmt_time_end_last":"2020-03-30 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"632576":{"#nid":"632576","#data":{"type":"event","title":"ARC Colloquium: Maryam Aliakbarpour","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMaryam Aliakbarpour (MIT)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, March 2, 2020\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 East - 10:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003EDistribution testing:\u0026nbsp; Classical and new paradigms\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003EOne of the most fundamental problems in learning theory is to view input data as random samples from an unknown distribution and then to make statistical inferences about the underlying distribution. In this talk, we focus on a notable example of such a statistical task: testing properties of distributions. The goal is to design an algorithm that uses as few samples as possible from a distribution and distinguishes whether the distribution has the property, or it is $\\epsilon$-far in $\\ell_1$-distance from any distribution which has the property. In this talk, we explore several questions in the framework of distribution testing, such as (i) Is the distribution uniform? Or, is it far from being uniform? (ii) Is a pair of random variables independent or correlated? (iii) Is the distribution monotone? Moreover, we discuss extensions of the standard testing framework to more practical settings. For instance, we consider the case where the sensitivity of the input samples (e.g., patients\u0026rsquo; medical records) requires the design of statistical tests that ensure the privacy of individuals. We address this case by designing differentially private testing algorithms for several testing questions with (nearly)-optimal sample complexities.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022http:\/\/www.mit.edu\/~maryama\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Distribution testing: Classical and new paradigms - Klaus 1116 East at 10am"}],"uid":"27544","created_gmt":"2020-02-18 14:08:09","changed_gmt":"2020-02-24 15:46:02","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2020-03-02T10:00:00-05:00","event_time_end":"2020-03-02T11:00:00-05:00","event_time_end_last":"2020-03-02T11:00:00-05:00","gmt_time_start":"2020-03-02 15:00:00","gmt_time_end":"2020-03-02 16:00:00","gmt_time_end_last":"2020-03-02 16:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"631856":{"#nid":"631856","#data":{"type":"event","title":"ARC Colloquium: Vedat Levi Alev (Waterloo)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EVedat Levi Alev (Waterloo)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, February 10, 2020\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 East - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003EImproved Analysis of Higher Order Random Walks and Applications\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003ELocal spectral expansion is a very useful method for arguing about the spectral properties of several random walk matrices over simplicial complexes. The motivation of this work is to extend this method to analyze the mixing times of Markov chains for combinatorial problems. Our main result is a sharp upper bound on the second eigenvalue of the down-up walk on a pure simplicial complex, in terms of the second eigenvalues of its links. We show some applications of this result in analyzing mixing times of Markov chains including sampling independent sets of a graph.\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\n(\u003Ca href=\u0022https:\/\/arxiv.org\/abs\/2001.02827\u0022\u003Ehttps:\/\/arxiv.org\/abs\/2001.02827\u003C\/a\u003E)\u003Cbr \/\u003E\r\nJoint work with: Lap Chi Lau\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/cs.uwaterloo.ca\/~vlalev\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Improved Analysis of Higher Order Random Walks and Applications - Klaus 1116 East at 11am"}],"uid":"27544","created_gmt":"2020-01-29 18:42:06","changed_gmt":"2020-02-03 21:10:51","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2020-02-10T11:00:00-05:00","event_time_end":"2020-02-10T12:00:00-05:00","event_time_end_last":"2020-02-10T12:00:00-05:00","gmt_time_start":"2020-02-10 16:00:00","gmt_time_end":"2020-02-10 17:00:00","gmt_time_end_last":"2020-02-10 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"631695":{"#nid":"631695","#data":{"type":"event","title":"ARC Colloquium: Semih Cayci (Ohio State University)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003ESemih Cayci (Ohio State University)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, February 3, 2020\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EGroseclose 402 - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003EBudget-Constrained Learning and Optimization with Bandit Feedback\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003EIn numerous decision processes such as algorithm portfolio design, adaptive routing and dynamic pricing, each action incurs a random cost and yields a random and potentially correlated reward, where the process continues until the total cost exceeds a resource constraint. Motivated by these applications, we investigate the budget-constrained bandit problem in which the decision-maker aims to maximize the expected total reward subject to a budget constraint on the total cost. For this problem, we show that logarithmic regret is achievable as long as moments of order \u003Cem\u003Ep\u003C\/em\u003E \u0026gt; 2 exist. In particular, we propose robust learning algorithms that incorporate linear estimators to extract and exploit the correlation between the cost and reward of an arm for optimal sample complexity. We prove that these algorithms achieve tight regret bounds, which are optimal up to a constant factor in the Gaussian case. In the second part, we focus on the time-constrained bandit problem, and allow the decision-maker to interrupt an ongoing task and forgo its immediate reward for a potentially faster alternative. We show that this controlled interrupt mechanism improves the total reward linearly over time for a broad class of completion time distributions. In order to learn the optimal action and interrupt strategy, we propose learning algorithms that exploit the information structure of the problem to achieve order-optimal regret. We show that these learning algorithms provide efficient solutions for boosting the time-efficiency of stochastic local search methods in various fundamental applications such as the \u003Cem\u003Ek\u003C\/em\u003E-SAT problem.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/www.semihcayci.com\/\u0022\u003ESpeaker\u0026#39;s Webpage \u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Budget-Constrained Learning and Optimization with Bandit Feedback - Groseclose 402 at 11:00am"}],"uid":"27544","created_gmt":"2020-01-27 14:51:48","changed_gmt":"2020-01-27 14:53:23","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2020-02-03T11:00:00-05:00","event_time_end":"2020-02-03T12:00:00-05:00","event_time_end_last":"2020-02-03T12:00:00-05:00","gmt_time_start":"2020-02-03 16:00:00","gmt_time_end":"2020-02-03 17:00:00","gmt_time_end_last":"2020-02-03 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"630873":{"#nid":"630873","#data":{"type":"event","title":"ARC Colloquium: Kuikui Liu(Univ. of Washington)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKuikui Liu (Univ. of Washington)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, January 27, 2020\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EGroseclose 402 - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003ESpectral Independence in High-Dimensional Expanders and Applications to the Hardcore Model\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EWe say a probability distribution \u0026micro; is spectrally independent if an associated correlation matrix has a bounded largest eigenvalue for the distribution and all of its conditional distributions. We prove that if \u0026micro; is spectrally independent, then the corresponding high dimensional simplicial complex is a local spectral expander. Using a line of recent works on mixing time of high dimensional walks on simplicial complexes [KM17; DK17; KO18; AL19], this implies that the corresponding Glauber dynamics mixes rapidly and generates (approximate) samples from \u0026micro;. As an application, we show that natural Glauber dynamics mixes rapidly (in polynomial time) to generate a random independent set from the hardcore model up to the uniqueness threshold. This improves the quasi-polynomial running time of Weitz\u0026rsquo;s deterministic correlation decay algorithm [Wei06] for estimating the hardcore partition function, also answering a long-standing open problem of mixing time of Glauber dynamics [LV97; LV99; DG00; Vig01; Eft+16].\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;Joint work with Nima Anari and Shayan Oveis Gharan\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/homes.cs.washington.edu\/~liukui17\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Spectral Independence in High-Dimensional Expanders and Applications to the Hardcore Model - Groseclose 402 at 11:00am"}],"uid":"27544","created_gmt":"2020-01-10 15:17:26","changed_gmt":"2020-01-13 19:00:01","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2020-01-27T11:00:00-05:00","event_time_end":"2020-01-27T12:00:00-05:00","event_time_end_last":"2020-01-27T12:00:00-05:00","gmt_time_start":"2020-01-27 16:00:00","gmt_time_end":"2020-01-27 17:00:00","gmt_time_end_last":"2020-01-27 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"626979":{"#nid":"626979","#data":{"type":"event","title":"ARC Colloquium: Samuel Hopkins(Berkeley)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003ESamuel Hopkins (Berkeley)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, December 2, 2019\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 East- 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003ERobust Mean Estimation in Nearly-Linear Time\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003ERobust mean estimation is the following basic estimation question: given i.i.d. copies of a random vector X in d-dimensional Euclidean space of which a small constant fraction are corrupted, how well can you estimate the mean of the distribution? This is a classical problem in statistics, going back to the 60\u0026#39;s and 70\u0026#39;s, and has recently found application to many problems in reliable machine learning. However, in high dimensions, classical algorithms for this problem either were (1) computationally intractable, or (2) lost poly(d) factors in their accuracy guarantees. Recently, polynomial time algorithms have been demonstrated for this problem that still achieve (nearly) optimal error guarantees. However, the running times of these algorithms were either at least quadratic in dimension or in 1\/(desired accuracy), running time overhead which renders them ineffective in practice. In this talk we give the first truly nearly linear time algorithm for robust mean estimation which achieves nearly optimal statistical performance. Our algorithm is based on the matrix multiplicative weights method. Based on joint work with Yihe Dong and Jerry Li, to appear in NeurIPS 2019.\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\n----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/www.samuelbhopkins.com\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Robust Mean Estimation in Nearly-Linear Time - Klaus 1116 East at 11am"}],"uid":"27544","created_gmt":"2019-10-01 19:21:52","changed_gmt":"2019-11-25 17:23:49","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2019-12-02T11:00:00-05:00","event_time_end":"2019-12-02T12:00:00-05:00","event_time_end_last":"2019-12-02T12:00:00-05:00","gmt_time_start":"2019-12-02 16:00:00","gmt_time_end":"2019-12-02 17:00:00","gmt_time_end_last":"2019-12-02 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"628202":{"#nid":"628202","#data":{"type":"event","title":"ARC Colloquium: Yuhao Yi(RPI)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EYuhao Yi (RPI)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, November 18, 2019\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 East- 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003EFast Approximation Algorithms and Complexity Analysis for Design of Networked Systems\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003EThis talk focuses on network design algorithms for optimizing average consensus dynamics, dynamics that are widely used for information di\ufb00usion and distributed coordination in networked control systems. Network design algorithms seek to modify the network to improve the performance of the dynamical system. This can be achieved by controlling a subset of vertices or adding\/removing edges in the network. We provide new algorithmic and hardness results for two network design problems. The \ufb01rst problem is selecting at most k vertices as leaders so as to minimize the steady-state variance of the system. We prove the NP-hardness of the problem, and propose a greedy algorithm with an approximation factor arbitrarily close to (1- k\/(k-1) 1\/e), which runs in nearly-linear time of km, where m is the number of edges. The second problem is adding at most k edges from a candidate edge set to minimize network entropy. This problem is equivalent to maximizing the log number of spanning trees in a connected graph. We propose an algorithm that runs in nearly-linear time of m with an approximation factor arbitrarily close to (1-1\/e), and we prove hardness of approximation of the problem. Finally, we summarize algorithmic and complexity results related to network design and discuss how our methods \ufb01t into context and also propose some ideas for future work.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/yhyi15.github.io\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Fast Approximation Algorithms and Complexity Analysis for Design of Networked Systems  - Klaus 1116 East at 11am"}],"uid":"27544","created_gmt":"2019-10-28 19:13:11","changed_gmt":"2019-11-07 20:39:01","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2019-11-18T11:00:00-05:00","event_time_end":"2019-11-18T12:00:00-05:00","event_time_end_last":"2019-11-18T12:00:00-05:00","gmt_time_start":"2019-11-18 16:00:00","gmt_time_end":"2019-11-18 17:00:00","gmt_time_end_last":"2019-11-18 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"628522":{"#nid":"628522","#data":{"type":"event","title":"ARC Colloquium: Xiaoming Huo (Georgia Tech)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EXiaoming Huo\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, November 11, 2019\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 East- 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003EHomotopic methods can significantly speed up the Computation of the Lasso-type of estimators\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003EIn optimization, it is well known that when the objective functions are strictly convex, gradient based approaches can be extremely effective, and most likely achieve the exponential rate in convergence. At the same time, the Lasso-type of estimator in general cannot achieve the optimal rate due to the undesirable behavior of the absolute function at the origin. The homotopic approach is to use a sequence of surrogate functions to approximate the L1 penalty in the Lasso-type of estimators. The approximating functions will converge to the L1 penalty in the Lasso estimator. At the same time, each approximating function is strictly convex and facilitates efficient numerical convergence. We demonstrate that by meticulously defined the surrogate functions, one can approve faster numerical convergence rate than any existing methods in computing for the Lasso-type of estimators. Our numerical simulations validate the above claim. We demonstrate the applications of the proposed methods in some cases.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/pwp.gatech.edu\/xiaoming-huo\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Homotopic methods can significantly speed up the Computation of the Lasso-type of estimators - Klaus 1116 East at 11am"}],"uid":"27544","created_gmt":"2019-11-04 12:57:10","changed_gmt":"2019-11-04 12:57:10","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2019-11-11T11:00:00-05:00","event_time_end":"2019-11-11T12:00:00-05:00","event_time_end_last":"2019-11-11T12:00:00-05:00","gmt_time_start":"2019-11-11 16:00:00","gmt_time_end":"2019-11-11 17:00:00","gmt_time_end_last":"2019-11-11 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"625917":{"#nid":"625917","#data":{"type":"event","title":"ARC Colloquium: Ravi Kumar (Google)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003ERavi Kumar (Google)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, November 4, 2019\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 East- 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003EAlgorithmic Discrete Choice\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003EIn this talk we consider random utility models for discrete choice.\u0026nbsp; In discrete choice, the task is to select exactly one element from a discrete set of alternatives.\u0026nbsp; We focus on algorithmic questions in this and related models, ranging from reconstructing the model parameters to identifiability of mixtures of models.\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\n----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/simons.berkeley.edu\/people\/ravi-kumar\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Algorithmic Discrete Choice - Klaus 1116 East at 11am"}],"uid":"27544","created_gmt":"2019-09-10 13:50:02","changed_gmt":"2019-10-09 12:30:29","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2019-11-04T11:00:00-05:00","event_time_end":"2019-11-04T12:00:00-05:00","event_time_end_last":"2019-11-04T12:00:00-05:00","gmt_time_start":"2019-11-04 16:00:00","gmt_time_end":"2019-11-04 17:00:00","gmt_time_end_last":"2019-11-04 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"623388":{"#nid":"623388","#data":{"type":"event","title":"ARC\/ACO Alumni Colloquium: Nikhil Devanur (Amazon)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EARC\/ACO Alumni Colloquium\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003ENikhil Devanur (Amazon)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, September 30, 2019\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 East- 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003ELagrangian Duality in Mechanism Design\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003EThis talk surveys the usage of Lagrangian Duality in the design and analysis of auctions.\u0026nbsp;Designing optimal (revenue maximizing) auctions in multi-parameter settings has been among the most active areas in algorithmic mechanism design in the last few years. We have discovered that Lagrangian duality is a very useful and versatile tool for this purpose. It has been used to do all of the following.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E1. Derive that the optimal auction is a virtual welfare maximizer.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E2. Obtain a fast algorithm for approximating the optimal auction.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E3. Show how simple auctions are approximately optimal.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E4. Characterize optimal auctions for structured environments.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E5. Get bounds on the menu-size complexity of optimal auctions.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EI will survey these applications and dive deeper into a subset of these.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/www.nikhildevanur.com\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Lagrangian Duality in Mechanism Design - Klaus 1116 East at 11am"}],"uid":"27544","created_gmt":"2019-07-15 19:09:09","changed_gmt":"2019-09-25 22:23:13","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2019-09-30T12:00:00-04:00","event_time_end":"2019-09-30T13:00:00-04:00","event_time_end_last":"2019-09-30T13:00:00-04:00","gmt_time_start":"2019-09-30 16:00:00","gmt_time_end":"2019-09-30 17:00:00","gmt_time_end_last":"2019-09-30 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"622978":{"#nid":"622978","#data":{"type":"event","title":"ARC Colloquium: Rong Ge (Duke)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003ERong Ge (Duke)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, October 28, 2019\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116E - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003EWhat 2-layer neural nets can we optimize?\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003EOptimizing neural networks is a highly nonconvex problem, and even optimizing a 2-layer neural network can be challenging. In the recent years many different approaches were proposed to learn 2-layer neural networks under different assumptions. This talk will give a brief survey on these approaches, and discuss some new results using spectral methods and optimization landscape.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/users.cs.duke.edu\/~rongge\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@cc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"What 2-layer neural nets can we optimize? - Klaus 1116 East at 11 am"}],"uid":"27544","created_gmt":"2019-07-03 13:36:39","changed_gmt":"2019-09-19 18:27:11","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2019-10-28T12:00:00-04:00","event_time_end":"2019-10-29T00:00:00-04:00","event_time_end_last":"2019-10-29T00:00:00-04:00","gmt_time_start":"2019-10-28 16:00:00","gmt_time_end":"2019-10-29 04:00:00","gmt_time_end_last":"2019-10-29 04:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"626033":{"#nid":"626033","#data":{"type":"event","title":"ARC Colloquium: Umang Bhaskar(TIFR)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EUmang Bhaskar (TIFR)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EFriday, October 18, 2019\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EGroseclose 402 - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle: \u003C\/strong\u003EPartial Function Extension with Applications to Learning and Property Testing\u003C\/p\u003E\r\n\r\n\u003Cdiv\u003E\u0026nbsp;\u003C\/div\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003EIn partial function extension, we are given a partial function consisting of points from a domain and a function value at each point.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EOur objective is to determine if this partial function can be extended to a total function defined on the domain, that additionally satisfies a given property, such as convexity. This basic problem underlies research questions in many areas, such as learning, property testing, and game theory. We present bounds on the complexity of partial function extension to subadditive, submodular, and convex functions, and present applications to learning as well as property testing for these functions.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThis is joint work with Gunjan Kumar.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/www.tcs.tifr.res.in\/~umang\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@cc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Partial Function Extension with Applications to Learning and Property Testing - Groseclose 402 at 11am"}],"uid":"27544","created_gmt":"2019-09-11 14:30:47","changed_gmt":"2019-09-18 15:11:55","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2019-10-18T12:00:00-04:00","event_time_end":"2019-10-18T13:00:00-04:00","event_time_end_last":"2019-10-18T13:00:00-04:00","gmt_time_start":"2019-10-18 16:00:00","gmt_time_end":"2019-10-18 17:00:00","gmt_time_end_last":"2019-10-18 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"622977":{"#nid":"622977","#data":{"type":"event","title":"ARC Colloquium: Thomas Rothvoss (UW)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EThomas Rothvoss (UW)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, October 7, 2019\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 East - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003ELinear Size Sparsifier and the Geometry of the Operator Norm Ball\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003EThe Matrix Spencer Conjecture asks whether given \u003Cem\u003En\u003C\/em\u003E symmetric matrices in \u211d\u003Cem\u003En\u003C\/em\u003E\u0026times;\u003Cem\u003En\u003C\/em\u003E with eigenvalues in [\u0026minus;1,1] one can always find signs so that their signed sum has singular values bounded by \u003Cem\u003EO\u003C\/em\u003E(\u003Cem\u003En\u003C\/em\u003E\u0026oline;\u0026radic;). The standard approach in discrepancy requires proving that the convex body of all good fractional signings is large enough. However, this question has remained wide open due to the lack of tools to certify measure lower bounds for rather small non-polyhedral convex sets.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EA seminal result by Batson, Spielman and Srivastava from 2008 shows that any undirected graph admits a linear size spectral sparsifier. Again, one can define a convex body of all good fractional signings. We can indeed prove that this body is close to most of the Gaussian measure. This implies that a discrepancy algorithm by the second author can be used to sample a linear size sparsifer. In contrast to previous methods, we require only a logarithmic number of sampling phases.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThis is joint work with Victor Reis.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/sites.math.washington.edu\/~rothvoss\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@cc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Linear Size Sparsifier and the Geometry of the Operator Norm Ball - Klaus 1116 East at 11am"}],"uid":"27544","created_gmt":"2019-07-03 13:31:46","changed_gmt":"2019-09-12 19:23:04","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2019-10-07T12:00:00-04:00","event_time_end":"2019-10-07T13:00:00-04:00","event_time_end_last":"2019-10-07T13:00:00-04:00","gmt_time_start":"2019-10-07 16:00:00","gmt_time_end":"2019-10-07 17:00:00","gmt_time_end_last":"2019-10-07 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"623038":{"#nid":"623038","#data":{"type":"event","title":"ARC Colloquium: Moses Charikar (Stanford)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMoses Charikar (Stanford)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, September 9, 2019\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 East- 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003EApproximating Profile Maximum Likelihood Efficiently\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003ESymmetric properties of distributions arise in multiple settings. For each of these, separate estimators and analysis techniques have been developed. Recently, Orlitsky et al showed that a single estimator that maximizes profile maximum likelihood (PML) is sample competitive for all symmetric properties. Further, they showed that even a 2^{n^{1-delta}}-approximate maximizer of the PML objective can serve as such a universal plug-in estimator. (Here n is the size of the sample). Unfortunately, no polynomial time computable PML estimator with such an approximation guarantee was known. We provide the first such estimator and show how to compute it in time nearly linear in n.\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\nJoint work with Kiran Shiragur and Aaron Sidford.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/engineering.stanford.edu\/people\/moses-charikar\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Approximating Profile Maximum Likelihood Efficiently - Klaus 1116 East at 11am"}],"uid":"27544","created_gmt":"2019-07-08 16:23:24","changed_gmt":"2019-09-04 12:26:21","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2019-09-09T12:00:00-04:00","event_time_end":"2019-09-09T13:00:00-04:00","event_time_end_last":"2019-09-09T13:00:00-04:00","gmt_time_start":"2019-09-09 16:00:00","gmt_time_end":"2019-09-09 17:00:00","gmt_time_end_last":"2019-09-09 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"623025":{"#nid":"623025","#data":{"type":"event","title":"ARC Colloquium: Shipra Agrawal (Columbia)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EShipra Agrawal (Columbia)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, September 23, 2019\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EGroseclose 402 - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003EThompson Sampling for learning in online decision making\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003EModern online marketplaces feed themselves. They rely on historical data to optimize content and user-interactions, but further, the data generated from these interactions is fed back into the system and used to optimize future interactions. As this cycle continues, good performance requires algorithms capable of learning actively through sequential interactions, systematically experimenting to improve future performance, and balancing this experimentation with the desire to make decisions with most immediate benefit. Thompson Sampling is a surprisingly simple and flexible Bayesian heuristic for handling this exploration-exploitation tradeoff in online decision problems. While this basic algorithmic technique can be traced back to 1933, the last five years have seen an unprecedented growth in the theoretical understanding as well as commercial interest in this method. In this talk, I will discuss our work in design and analysis of Thompson Sampling based algorithms for several classes of multi-armed bandits, online assortment selection, and reinforcement learning learning problems. We demonstrate that natural versions of the Thompson Sampling heuristic achieve near-optimal theoretical performance bounds for these problems, along with attractive empirical performance.\u003C\/p\u003E\r\n\r\n\u003Cdiv\u003EThis talk is based on joint works with Vashist Avadhanula, Navin Goyal, Vineet Goyal, Randy Jia, and Assaf Zeevi.\u003C\/div\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022http:\/\/www.columbia.edu\/~sa3305\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@cc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Thompson Sampling for learning in online decision making - Groseclose 402 at 11am"}],"uid":"27544","created_gmt":"2019-07-08 12:48:45","changed_gmt":"2019-09-03 19:14:44","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2019-09-23T12:00:00-04:00","event_time_end":"2019-09-23T13:00:00-04:00","event_time_end_last":"2019-09-23T13:00:00-04:00","gmt_time_start":"2019-09-23 16:00:00","gmt_time_end":"2019-09-23 17:00:00","gmt_time_end_last":"2019-09-23 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"623384":{"#nid":"623384","#data":{"type":"event","title":"ARC Colloquium: Jelani Nelson (UC Berkeley)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EJelani Nelson (UC Berkeley)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, September 16, 2019\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EGroseclose 402- 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003ESome new approaches to the heavy hitters problem\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003EIn the \u0026#39;frequent items\u0026#39; problem one sees a sequence of items in a stream (e.g. a stream of words coming into a search query engine like\u003C\/p\u003E\r\n\r\n\u003Cp\u003EGoogle) and wants to report a small list of items containing all frequent items. In the \u0026#39;change detection\u0026#39; problem one sees two streams, say one from yesterday and one from today, and wants to report a small list of items containing all those whose frequencies changed significantly. For both of these problems, we would like algorithms that use memory substantially sublinear in the length of the stream.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EWe describe new state-of-the-art solutions to both problems. For the former, we make use of chaining methods to control the suprema of Rademacher processes to develop an algorithm BPTree with provably near-optimal memory consumption. For the latter, we develop the first algorithm to simultaneously achieve asymptotically optimal space, fast query and update time, and high success probability (over the random coins flipped by the algorithm) by reducing the problem to a certain graph partitioning problem, which we then give a new algorithm for.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EBased on joint works with Vladimir Braverman, Stephen Chestnut, Nikita Ivkin, Kasper Green Larsen, Huy Le Nguyen, Mikkel Thorup, Zhengyu Wang, and David P. Woodruff\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/people.eecs.berkeley.edu\/~minilek\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@cc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Some new approaches to the heavy hitters problem - Groseclose 402 at 11am"}],"uid":"27544","created_gmt":"2019-07-15 19:03:23","changed_gmt":"2019-08-28 18:05:55","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2019-09-16T12:00:00-04:00","event_time_end":"2019-09-16T13:00:00-04:00","event_time_end_last":"2019-09-16T13:00:00-04:00","gmt_time_start":"2019-09-16 16:00:00","gmt_time_end":"2019-09-16 17:00:00","gmt_time_end_last":"2019-09-16 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"622974":{"#nid":"622974","#data":{"type":"event","title":"ARC Colloquium: Aleksandar Nikolov (Univ. of Toronto)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAleksandar Nikolov (Univ. of Toronto)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, August 19, 2019\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 East - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003EThe Power of Factorization Mechanisms in Differential Privacy\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003EA central goal in private data analysis is to estimate statistics about an unknown distribution from a dataset possibly containing sensitive information, so that the privacy of any individual represented in the dataset is preserved. We study this question in the model of non-interactive local differential privacy (LDP), in which every person in the dataset randomizes their own data in order to preserve its privacy, before sending it to a central server. We give a characterization of the minimum number of samples necessary to get an accurate estimates of a given set of statistical queries, as well as a characterization of the sample complexity of agnostic PAC learning in this model. The characterization is tight up polylogarithmic factors for any given set of statistical queries, respectively any given concept class. The characterization is achieved by a simple and efficient instance-optimal (with respect to the queries\/concept class) approximate factorization mechanism, i.e. a mechanism that answers the statistical queries by answering a different set of strategy queries from which the answers to the original queries can be approximately reconstructed. We also show that factorization mechanisms are instance optimal in some parameter regimes in the central curator model of differential privacy.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EBased on joint work with Alexander Edmonds and Jonathan Ullman\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022http:\/\/www.cs.toronto.edu\/~anikolov\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@cc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"The Power of Factorization Mechanisms in Differential Privacy - Klaus 1116 East at 11am "}],"uid":"27544","created_gmt":"2019-07-03 13:23:48","changed_gmt":"2019-08-13 13:50:36","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2019-08-19T12:00:00-04:00","event_time_end":"2019-08-19T13:00:00-04:00","event_time_end_last":"2019-08-19T13:00:00-04:00","gmt_time_start":"2019-08-19 16:00:00","gmt_time_end":"2019-08-19 17:00:00","gmt_time_end_last":"2019-08-19 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"620313":{"#nid":"620313","#data":{"type":"event","title":"ARC-IISP Colloquium: Richard DeMillo (Georgia Tech)","body":[{"value":"\u003Cp align=\u0022center\u0022\u003E\u003Ca href=\u0022http:\/\/arc.gatech.edu\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/a\u003E and\u003C\/p\u003E\r\n\r\n\u003Cp align=\u0022center\u0022\u003E\u003Ca href=\u0022http:\/\/cyber.gatech.edu\/\u0022\u003E\u003Cstrong\u003EInstitute for Information Security \u0026amp; Privacy (IISP)\u003C\/strong\u003E\u003C\/a\u003E\u0026nbsp;\u003Cstrong\u003E Colloquium\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003ERichard A. DeMillo (Georgia Tech)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EMonday, May 13, 2019\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EMiRC Pettit 102 -- 11am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022http:\/\/arc.gatech.edu\/node\/349\u0022\u003EPowerpoint of slides from Rich DeMillo\u0027s May 13, 2019 colloquium\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle: \u0026nbsp;\u003C\/strong\u003EThe Difficult Problem of Simply Voting\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp;\u0026nbsp;\u003C\/strong\u003EElections seem pretty simple: People show up on election day to vote for one candidate or another. A good election system has to accurately count the number of votes for each candidate and report the totals to the public while ensuring that\u003C\/p\u003E\r\n\r\n\u003Cp\u003EV1\u0026nbsp; Elections are fair\u003Cbr \/\u003E\r\nV2\u0026nbsp; Everyone\u0026#39;s votes are secret,\u003Cbr \/\u003E\r\nV3\u0026nbsp; Only eligible votes are counted\u003Cbr \/\u003E\r\nV4\u0026nbsp; No one votes more than once\u003Cbr \/\u003E\r\nV5\u0026nbsp; Ballots, once cast, are not altered, lost, or destroyed\u003C\/p\u003E\r\n\r\n\u003Cp\u003EMany people believe that, in an Internet-enabled world, secure, safe voting should be easy to achieve. For example, using known cryptographically secure protocols (maybe even blockchains), a secure website might be developed to relieve voters of the burden of driving to a polling place on election day. While we\u0026#39;re at it, we can probably improve on the election algorithm itself, since there is a rich literature on fair voting schemes that more accurately and reliably reflect actual voter preferences.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EExcept that:\u003C\/p\u003E\r\n\r\n\u003Cp\u003EE1\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; There is no one in charge of elections. The U.S. Constitution delegates that authority to states and localities. A national election is more than 10,000 independent elections, each one operating autonomously, using its own rules.\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\nE2\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; Because casting,\u0026nbsp; recording and counting votes is an error-prone human process, the losing candidate is often not convinced that the result is accurate. Although no one trusts anyone else, elections should generate public evidence to convince those who voted for the loser that another candidate won.\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\nE3\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; The scale and complexity of American elections require computerization of the voting process, and computers can be hacked or misprogrammed\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\nE4\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; The only known methods for protecting voting computers rely on math and technology, but the average voter does not understand math or technology\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\nWe now know that there are active, well-funded adversaries who are trying to disrupt elections with information and cyber attacks on election systems. E1-E4 prohibit many security-enhancing simplifications and therefore complicate the problem of conducting modern elections in such an environment.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThe most widely accepted method for ensuring that errors in tabulating votes (whether malicious or inadvertent) is the Risk-Limiting Audit (RLA), a post-election, sequential sampling process that for some predetermined risk limit \u0026alpha;: confirms an error-free tabulation with probability 1 and fails to confirm an incorrect tabulation with probability at least 1-\u0026alpha;. The most widely accepted necessary condition for securely marking and tabulating ballots is software independence (an undetected error in voting software cannot result in an undetectable change in reported vote totals).\u003C\/p\u003E\r\n\r\n\u003Cp\u003ETwo competing election systems purport to be auditable and software independent: hand-marked paper ballots and paper ballots printed by machines called Ballot Marking Devices (BMDs). In this talk, I will discuss recent work with Andrew Appel and Philip Stark, arguing that BMDs are neither software\u003Cbr \/\u003E\r\nindependent nor meaningfully auditable by RLAs. We also introduce two new conditions called contestability and defensibility that are necessary for an audit to confirm election results.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022http:\/\/www.c21u.gatech.edu\/team\/faculty\/demillo\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at:\u0026nbsp;\u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@cc.gatech.edu\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"The Difficult Problem of Simply Voting - MiRC Pettit 102 at 11am"}],"uid":"32895","created_gmt":"2019-04-11 13:43:32","changed_gmt":"2019-05-21 18:55:14","author":"Eric Vigoda","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2019-05-13T12:00:00-04:00","event_time_end":"2019-05-13T13:00:00-04:00","event_time_end_last":"2019-05-13T13:00:00-04:00","gmt_time_start":"2019-05-13 16:00:00","gmt_time_end":"2019-05-13 17:00:00","gmt_time_end_last":"2019-05-13 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"621524":{"#nid":"621524","#data":{"type":"event","title":"ARC Colloquium: Yin Tat Lee(UW)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EYin Tat Lee (UW)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, May 20, 2019\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116E - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003ESolving Linear Programs in the Current Matrix Multiplication Time\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003EWe show how to solve linear programs with accuracy epsilon in time n^{omega+o(1)} log(1\/epsilon) where omega~2.3728639 is the current matrix multiplication constant. This hits a natural barrier of solving linear programs since linear systems is a special case of linear programs and solving linear systems require time n^{omega} currently.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EJoint work with Michael B. Cohen and Zhao Song.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022http:\/\/yintat.com\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@cc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Solving Linear Programs in the Current Matrix Multiplication Time - Klaus 1116 East at 11 am"}],"uid":"27544","created_gmt":"2019-05-08 19:05:04","changed_gmt":"2019-05-08 19:05:04","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2019-05-20T12:00:00-04:00","event_time_end":"2019-05-20T13:00:00-04:00","event_time_end_last":"2019-05-20T13:00:00-04:00","gmt_time_start":"2019-05-20 16:00:00","gmt_time_end":"2019-05-20 17:00:00","gmt_time_end_last":"2019-05-20 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"619099":{"#nid":"619099","#data":{"type":"event","title":"ARC Colloquium: Will Perkins (UIC)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EWill Perkins (UIC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, May 6, 2019\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116E - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003EAbstract polymer models, the cluster expansion, and applications\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003EI will give two lectures introducing abstract polymer models and the cluster expansion from statistical physics.\u0026nbsp; I will describe some of the original applications of these tools in statistical physics to understand phase transitions in lattice spin systems, and then present applications of these tools in combinatorics (understanding complex zeros of graph polynomials) and computer science (approximate counting problems).\u0026nbsp; The lectures will be accessible to graduate students in combinatorics, probability, and computer science and will include several directions for future work.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022http:\/\/willperkins.org\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@cc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Abstract polymer models, the cluster expansion, and applications  - Klaus 1116 East at 11 am"}],"uid":"27544","created_gmt":"2019-03-11 17:56:50","changed_gmt":"2019-04-03 13:41:58","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2019-05-06T12:00:00-04:00","event_time_end":"2019-05-06T13:00:00-04:00","event_time_end_last":"2019-05-06T13:00:00-04:00","gmt_time_start":"2019-05-06 16:00:00","gmt_time_end":"2019-05-06 17:00:00","gmt_time_end_last":"2019-05-06 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"619186":{"#nid":"619186","#data":{"type":"event","title":"ARC Lecture Series: Ola Svensson (EPFL)","body":[{"value":"\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EBreakthroughs in Approximation Algorithms for\u003Cbr \/\u003E\r\nTraveling Salesman Problems (TSP)\u0026nbsp;\u003C\/strong\u003E\u003Cbr \/\u003E\r\nLecture series by\u0026nbsp;\u003Ca href=\u0022https:\/\/theory.epfl.ch\/osven\/\u0022\u003EOla Svensson (EPFL)\u003C\/a\u003E\u003Cbr \/\u003E\r\nTuesday, April 23 - Thursday, April 25, 2019\u003Cbr \/\u003E\r\n10am - noon daily in Groseclose 402\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cbr \/\u003E\r\n\u003Cstrong\u003E\u003Cem\u003ESchedule:\u003C\/em\u003E\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003ETuesday, April 23, 2019\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E10:00am - 12:00pm\u0026nbsp;\u0026nbsp;\u0026nbsp; Lecture 1: The symmetric TSP (Groseclose 402)\u003Cbr \/\u003E\r\n12:00pm - 1:00pm \u0026nbsp; \u0026nbsp;\u0026nbsp; Lunch\u003Cbr \/\u003E\r\n3:30pm - 4:00pm\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; Problem Solving Session (Klaus 2222)\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EWednesday, April 24, 2019\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E10:00am - 12:00pm\u0026nbsp;\u0026nbsp;\u0026nbsp; Lecture 2: \u0026nbsp;Different approaches for asymmetric TSP (Groseclose 402)\u003Cbr \/\u003E\r\n12:00pm - 1:00pm\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; Lunch\u0026nbsp;\u0026amp; Poster Session\u003Cbr \/\u003E\r\n3:30pm - 4:00pm\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; Problem Solving Session (Klaus 2222)\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EThursday, April 25, 2019\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E10:00am - 12:00pm\u0026nbsp;\u0026nbsp;\u0026nbsp; Lecture 3: A constant-factor approximation algorithm for asymmetric TSP (Groseclose 402)\u003Cbr \/\u003E\r\n12:00pm - 1:00pm\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; Lunch\u003Cbr \/\u003E\r\n3:30pm - 4:00pm\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; Problem Solving Session (Klaus 2222)\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp;\u0026nbsp;\u003C\/strong\u003EThe traveling salesman problem is one of the most fundamental optimization problems. Given n cities and pairwise distances, it is the problem of finding a tour of minimum distance that visits each city once. In spite of significant research efforts, current techniques seem insufficient for settling the approximability of the traveling salesman problem.\u0026nbsp; This status is particularly intriguing as a natural and several-decade-old linear programming relaxation is believed to give better guarantees than we are currently able to prove!\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIn this mini-course, we will overview of old and new approaches for settling this question. We shall, in particular, talk about recent developments for the asymmetric traveling salesman problem.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EBio:\u0026nbsp;\u0026nbsp;\u003C\/strong\u003EOla Svensson is an Associate Professor at the School of Computer and Communication Sciences at EPFL, Switzerland.\u0026nbsp; He is interested in theoretical aspects of computer science with an emphasis on the approximability of NP-hard optimization problems. His work has received several recognitions including the 2019 Michael and Sheila Held Prize by the National Academy of Sciences and best paper awards at FOCS and STOC\u003Cstrong\u003E. \u0026nbsp;\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/theory.epfl.ch\/osven\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@cc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Breakthroughs in Approximation Algorithms for Traveling Salesman Problems (TSP)  - Groseclose 402"}],"uid":"27544","created_gmt":"2019-03-13 15:04:01","changed_gmt":"2019-04-01 00:55:36","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2019-04-23T11:00:00-04:00","event_time_end":"2019-04-25T14:00:00-04:00","event_time_end_last":"2019-04-25T14:00:00-04:00","gmt_time_start":"2019-04-23 15:00:00","gmt_time_end":"2019-04-25 18:00:00","gmt_time_end_last":"2019-04-25 18:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"619416":{"#nid":"619416","#data":{"type":"event","title":"ARC Colloquium: Kunal Talwar (Google)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKunal Talwar (Google)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, April 1, 2019\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116E - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003EAmplification Theorems for Differentially Private Machine Learning\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003EA rigorous foundational approach to private data analysis has emerged in theoretical computer science in the last decade, with differential privacy and its close variants playing a central role. We have recently been able to train complex machine learning models with little accuracy loss, while giving strong differentially privacy guarantees. The analyses of these algorithms rely on a class of results known as privacy amplification theorems. In this talk, I will sketch how private ML models can be trained, and how they can be analysed. I will then describe two recent privacy amplification theorems, and some of their implications.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E(Joint works with Ulfar Erlingsson, Vitaly Feldman, Ilya Mironov, Ananth Raghunathan and\u0026nbsp; Abhradeep Thakurta)\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022http:\/\/kunaltalwar.org\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@cc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Amplification Theorems for Differentially Private Machine Learning - Klaus 1116 East at 11 am"}],"uid":"27544","created_gmt":"2019-03-19 15:22:27","changed_gmt":"2019-03-26 13:19:33","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2019-04-01T12:00:00-04:00","event_time_end":"2019-04-01T13:00:00-04:00","event_time_end_last":"2019-04-01T13:00:00-04:00","gmt_time_start":"2019-04-01 16:00:00","gmt_time_end":"2019-04-01 17:00:00","gmt_time_end_last":"2019-04-01 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1789","name":"Conference\/Symposium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"618789":{"#nid":"618789","#data":{"type":"event","title":"ARC Colloquium: Ravi Kannan (MSR)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003ERavi Kannan (MSR)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, March 25, 2019\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116E - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003EA General Algorithm for Unsupervised Learning problems\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003EThe following simply-stated geometric problem includes as special cases the core problems of a\u0026nbsp; number\u0026nbsp; of\u0026nbsp; areas\u0026nbsp; in\u0026nbsp; Unsupervised\u0026nbsp; Learning,\u0026nbsp; including,\u0026nbsp; Topic\u0026nbsp; Modeling,\u0026nbsp; Non-negative\u0026nbsp; Matrix Factorization, Clustering, Stochastic Block Models and Overalapping Communities Detection:\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThere is an unknown polytope \u003Cem\u003EK\u003C\/em\u003E\u0026nbsp; \u0026isin; \u003Cstrong\u003ER\u003C\/strong\u003E\u003Cem\u003E\u003Csup\u003Ed\u003C\/sup\u003E\u003C\/em\u003E with\u003Cem\u003E k\u003C\/em\u003E vertices.\u0026nbsp; We are given n data points, each aperturbation of some point in \u003Cem\u003EK.\u003C\/em\u003E\u0026nbsp; The problem is to find \u003Cem\u003EK\u003C\/em\u003E, i.e., its vertices (approximately).\u0026nbsp; [The perturbations are large; indeed, many data points lie outside\u003Cem\u003E K\u003C\/em\u003E.]\u003C\/p\u003E\r\n\r\n\u003Cp\u003EOur main result is an algorithm which solves this general problem under two natural assumptions.\u0026nbsp; Our assumptions are technically different,\u0026nbsp; but similar in spirit to existing models for the special cases.\u0026nbsp; We assume separation between the vertices of\u003Cem\u003E K\u003C\/em\u003E\u0026nbsp; and the existence of \u0026ldquo;pure\u0026rdquo; data points whose unperturbed versions are close to the vertices of \u003Cem\u003EK\u003C\/em\u003E.\u0026nbsp; Notably we do not assume any stochastic\u0026nbsp; model\u0026nbsp; of\u0026nbsp; data.\u0026nbsp;\u0026nbsp; Our\u0026nbsp; algorithm\u0026nbsp; has\u0026nbsp; better\u0026nbsp; complexity\u0026nbsp; than\u0026nbsp; known\u0026nbsp; algorithms\u0026nbsp; for\u0026nbsp; the special cases when the input matrix\u003Cstrong\u003E A\u003C\/strong\u003E is sparse and k is relatively small compared to \u003Cem\u003En, d\u003C\/em\u003E.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThe algorithm is simply stated, but the proof of correctness is involved.\u0026nbsp; It draws on tools in Numerical Analysis, especially perturbation of singular spaces of matrices.\u0026nbsp; Here is a description of our algorithm:\u0026nbsp; It has \u003Cem\u003Ek\u003C\/em\u003E stages; in each stage, it picks a certain random vector \u003Cem\u003Eu\u003C\/em\u003E, finds the \u003Cem\u003Em\u003C\/em\u003E largest\u003Cem\u003E u \u0026middot; x \u003C\/em\u003Eover data points\u003Cem\u003E x\u003C\/em\u003E and outputs the average of these data points as an approximation to a new vertex of \u003Cem\u003EK\u003C\/em\u003E.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EJoint Work with C. Bhattacharyya\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/simons.berkeley.edu\/people\/ravi-kannan\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@cc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"A General Algorithm for Unsupervised Learning problems - Klaus 1116 East at 11 am"}],"uid":"27544","created_gmt":"2019-03-05 14:33:45","changed_gmt":"2019-03-19 12:35:05","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2019-03-25T12:00:00-04:00","event_time_end":"2019-03-25T13:00:00-04:00","event_time_end_last":"2019-03-25T13:00:00-04:00","gmt_time_start":"2019-03-25 16:00:00","gmt_time_end":"2019-03-25 17:00:00","gmt_time_end_last":"2019-03-25 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1789","name":"Conference\/Symposium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"617665":{"#nid":"617665","#data":{"type":"event","title":"ARC Colloquium: Konstantin Tikhomirov (Georgia Tech)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKonstantin Tikhomirov\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, March 4, 2019\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116E - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003ESingularity of Bernoulli random matrices\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003EAbstract: Let X_1,X_2,...,X_n be independent random vectors uniformly distributed on vertices of the n-dimensional cube [-1,1]^n. What is the probability that the vectors are linearly dependent? The question has been studied in the literature since 1960-es, and it was conjectured that\u003C\/p\u003E\r\n\r\n\u003Cp\u003EP{the vectors are linearly dependent}=(0.5+o(1))^n.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIn this talk, we will discuss a proof of this conjecture based on analysis of the associated random matrix.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022http:\/\/people.math.gatech.edu\/~ktikhomirov6\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@cc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Singularity of Bernoulli random matrices - Klaus 1116E at 11 am"}],"uid":"27544","created_gmt":"2019-02-12 16:04:12","changed_gmt":"2019-02-25 13:33:41","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2019-03-04T11:00:00-05:00","event_time_end":"2019-03-04T12:00:00-05:00","event_time_end_last":"2019-03-04T12:00:00-05:00","gmt_time_start":"2019-03-04 16:00:00","gmt_time_end":"2019-03-04 17:00:00","gmt_time_end_last":"2019-03-04 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1789","name":"Conference\/Symposium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"607352":{"#nid":"607352","#data":{"type":"event","title":"ARC Distinguished Lecture: \u00c9va Tardos (Cornell)","body":[{"value":"\u003Cp align=center\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align=center\u003E\u003Cstrong\u003E\u0026Eacute;va Tardos (Cornell)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align=center\u003E\u003Cstrong\u003EMonday, February 11, 2019\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align=center\u003E\u003Cstrong\u003EKlaus 1116 East \u0026amp; West \u0026ndash; 10:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003ELearning and Efficiency of Outcomes in Games\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u0026nbsp; Selfish behavior can often lead to suboptimal outcome for all participants, a phenomenon illustrated by many classical examples in game theory.\u0026nbsp; Over the last decade we have studied Nash equilibria of games, and developed good understanding how to quantify the impact of strategic user behavior on overall performance in many games (including traffic routing as well as online auctions). In this talk we will focus on games where players use a form of learning that helps them adapt to the environment. We ask if the quantitative guarantees obtained for Nash equilibria extend to such out of equilibrium game play, or \u0026nbsp;even more broadly, when the game or the population of players is dynamically changing and where participants have to adapt to the dynamic environment.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022http:\/\/www.cs.cornell.edu\/~eva\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@cc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Learning and Efficiency of Outcomes in Games - Klaus 1116 E \u0026 W at 10 am"}],"uid":"27544","created_gmt":"2018-06-27 19:39:37","changed_gmt":"2019-02-08 20:39:10","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2019-02-11T10:00:00-05:00","event_time_end":"2019-02-11T11:00:00-05:00","event_time_end_last":"2019-02-11T11:00:00-05:00","gmt_time_start":"2019-02-11 15:00:00","gmt_time_end":"2019-02-11 16:00:00","gmt_time_end_last":"2019-02-11 16:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"611722":{"#nid":"611722","#data":{"type":"event","title":"ARC Colloquium: Venkat Guruswami (CMU)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EVenkat Guruswami\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, December 3, 2018\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116E - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003EThe polymorphic gateway between structure and algorithms: Beyond\u0026nbsp;CSPs\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u0026nbsp; What underlying mathematical structure (or lack thereof) in a computational problem governs its efficient solvability (or dictates its hardness)? In the realm of constraint satisfaction problems (CSPs), the algebraic dichotomy theorem gives a definitive answer: a polynomial time algorithm exists when there are\u0026nbsp;non-trivial\u0026nbsp;local\u0026nbsp;operations called polymorphisms under which the solution space is closed; otherwise the problem is NP-complete.\u0026nbsp;Inspired and emboldened by this, one might speculate a broader polymorphic principle: if there are interesting ways to combine solutions to get more solutions, then the problem ought to be tractable (with context dependent interpretations of\u0026nbsp;\u0026quot;interesting\u0026quot; and \u0026quot;tractable\u0026rdquo;).\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EBeginning with some background on the polymorphic approach to understanding the complexity of constraint satisfaction, the talk will discuss some extensions\u0026nbsp;beyond CSPs where the polymorphic principle seems promising (yet far from understood). Specifically, we will discuss promise CSPs where one is allowed to satisfy a relaxed version of the constraints (a framework that includes important problems like approximate graph coloring and discrepancy minimization), and the potential and challenges in applying the polymorphic framework to them. Another interesting direction is fine-grained complexity, where partial polymorphisms govern the runtime of fast exponential-time algorithms. Our inquiries into these directions also reveal some interesting connections to optimization, such as algorithms to solve LPs over different rings (like integers adjoined with sqrt{2}), and a random-walk based algorithm interpolating between 0-1 and linear programming, generalizing\u0026nbsp;Sch\u0026ouml;ning\u0026#39;s\u0026nbsp;famous (4\/3)^n time algorithm for 3-SAT.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EBased\u0026nbsp;on a body of work with Joshua Brakensiek.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022http:\/\/www.cs.cmu.edu\/~venkatg\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@cc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"The polymorphic gateway between structure and algorithms: Beyond CSPs - Klaus 1116E at 11 am"}],"uid":"27544","created_gmt":"2018-09-20 14:58:53","changed_gmt":"2018-11-19 20:36:45","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2018-12-03T11:00:00-05:00","event_time_end":"2018-12-03T12:00:00-05:00","event_time_end_last":"2018-12-03T12:00:00-05:00","gmt_time_start":"2018-12-03 16:00:00","gmt_time_end":"2018-12-03 17:00:00","gmt_time_end_last":"2018-12-03 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"610220":{"#nid":"610220","#data":{"type":"event","title":"ARC-TRIAD Colloquium: Michael Mitzenmacher (Harvard)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EARC-TRIAD Colloquium\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMichael Mitzenmacher\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, November 26, 2018\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 East \u0026ndash; 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003EBloom Filters, Cuckoo Hashing, Cuckoo Filters, Adaptive Cuckoo Filters, and Learned Bloom Filters\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u0026nbsp; I will go over some of my past and present work on hashing-based data structures.\u0026nbsp; After presenting some background on Bloom filters and cuckoo hashing, we will describe cuckoo filters, an efficient data structure for approximate set membership that improves on the well-known Bloom filter. We then discuss recent work on how to make cuckoo filters adaptive in response to false positives, which can be important for many practical problems.\u0026nbsp; Finally, I will present some very recent work on how to possibly improve Bloom filters and related data structures using machine learning techniques.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022http:\/\/www.eecs.harvard.edu\/~michaelm\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@cc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Bloom Filters, Cuckoo Hashing, Cuckoo Filters, Adaptive Cuckoo Filters, and Learned Bloom Filters - Klaus 1116E at 11 am"}],"uid":"27544","created_gmt":"2018-08-23 12:03:55","changed_gmt":"2018-11-02 18:00:23","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2018-11-26T11:00:00-05:00","event_time_end":"2018-11-26T12:00:00-05:00","event_time_end_last":"2018-11-26T12:00:00-05:00","gmt_time_start":"2018-11-26 16:00:00","gmt_time_end":"2018-11-26 17:00:00","gmt_time_end_last":"2018-11-26 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"611936":{"#nid":"611936","#data":{"type":"event","title":"ARC Colloquium: Sampath Kannan (UPenn)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003ESampath Kannan\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, October 29, 2018\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 East \u0026ndash; 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003EFairness in Algorithmic Decision Making\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u0026nbsp; In this talk we survey some formulations of fairness requirements for decision making under uncertainty. We then discuss results from 3 recent papers:\u003C\/p\u003E\r\n\r\n\u003Cp\u003E1) Treating individuals fairly is not in conflict with long-term scientific learning goals if the population is sufficiently diverse.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E2) When there is a pipeline of decisions, end-to-end fairness is impossible to achieve even in a very simple model.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E3) Exploiting the knowledge acquired by others can unfairly advantage the free rider.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThese papers are joint work with a number of co-authors:\u003C\/p\u003E\r\n\r\n\u003Cp\u003EChristopher Jung, Neil Lutz, Jamie Morgenstern, Aaron Roth, Bo Waggoner, Steven Wu, and Juba Ziani\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/www.cis.upenn.edu\/~kannan\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@cc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":" Fairness in Algorithmic Decision Making - Klaus 1116 East at 11 am"}],"uid":"27544","created_gmt":"2018-09-25 18:22:44","changed_gmt":"2018-10-09 12:12:33","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2018-10-29T12:00:00-04:00","event_time_end":"2018-10-29T13:00:00-04:00","event_time_end_last":"2018-10-29T13:00:00-04:00","gmt_time_start":"2018-10-29 16:00:00","gmt_time_end":"2018-10-29 17:00:00","gmt_time_end_last":"2018-10-29 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"607600":{"#nid":"607600","#data":{"type":"event","title":"ARC-TRIAD Colloquium: Mary Wootters (Stanford)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EARC-TRIAD Colloquium\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMary Wootters\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, October 1, 2018\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMiRC Pettit 102A\u0026amp;B - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003EImproved Decoding of Folded Reed-Solomon and Multiplicity Codes\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u0026nbsp; List-decoding is an important primitive in the theory of error correcting codes, and it has long been a goal to obtain explicit constructions of capacity-achieving, efficiently list-decodable codes.\u0026nbsp; Folded Reed-Solomon Codes (Guruswami-Rudra 2008) and Multiplicity codes (Guruswami-Wang 2011, Kopparty 2012) are two such constructions.\u0026nbsp; However, previous analysis of these codes could not guarantee optimal parameters.\u0026nbsp; In particular, the \u0026ldquo;list-size\u0026rdquo; of these codes was only shown to be polynomial, while ideally it would be constant.\u0026nbsp; Thus, over the past decade or so, there have been several modifications of these codes aimed at reducing the list size to constant.\u0026nbsp; In this work, we show that in fact the list-sizes were constant all along, with no modifications required!\u0026nbsp; Further, we use our result for univariate multiplicity codes to establish improved local list-decoding results for multivariate multiplicity codes.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIn this talk, I\u0026rsquo;ll define all the terms in the paragraph above (in particular, no prior knowledge of error correcting codes is necessary!), and sketch the proofs of the results mentioned above.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EJoint work with Swastik Kopparty, Noga Ron-Zewi, and Shubhangi Saraf.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/sites.google.com\/site\/marywootters\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@cc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Improved Decoding of Folded Reed-Solomon and Multiplicity Codes - MiRC Pettit 102 A\u0026B at 11 am"}],"uid":"27544","created_gmt":"2018-07-10 14:31:26","changed_gmt":"2018-10-01 13:10:14","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2018-10-01T12:00:00-04:00","event_time_end":"2018-10-01T13:00:00-04:00","event_time_end_last":"2018-10-01T13:00:00-04:00","gmt_time_start":"2018-10-01 16:00:00","gmt_time_end":"2018-10-01 17:00:00","gmt_time_end_last":"2018-10-01 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1792","name":"Arts and Performance"},{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"607350":{"#nid":"607350","#data":{"type":"event","title":"ARC-TRIAD Colloquium: Leslie Valiant (Harvard)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EARC-TRIAD Colloquium\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003ELeslie Valiant\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, October 22, 2018\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 East \u0026amp; West\u0026nbsp; \u0026ndash; 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003EWhere Computer Science Meets Neuroscience\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u0026nbsp; For some problems in science there are several plausible theories and it remains to experimenters to determine which of them, if any, are valid. There exist other problems for which, in contrast, no known theory is widely accepted as plausible. Currently computational neuroscience is a field full of opportunity that offers several fundamental problems of the latter kind. We shall discuss one of these problems: Over a lifetime the brain performs hundreds of thousands of individual cognitive acts, of a variety of kinds, including the formation of new associations. Each such act depends on past experience, and, in turn, can have long lasting effects on future behavior. It is difficult to reconcile such large scale capabilities, including fast reaction times on new inputs when using knowledge acquired at various earlier times, with the known resource constraints on cortex, such as low connectivity and low average synaptic strength. Here we shall describe an approach to this fundamental problem that attempts to explain these phenomena in terms of concrete algorithms for a model of computation that is faithful to the most basic quantitative resources.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/www.seas.harvard.edu\/directory\/valiant\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@cc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Where Computer Science Meets Neuroscience - Klaus 1116 E \u0026 W at 11 am"}],"uid":"27544","created_gmt":"2018-06-27 19:15:09","changed_gmt":"2018-10-01 13:07:01","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2018-10-22T12:00:00-04:00","event_time_end":"2018-10-22T13:00:00-04:00","event_time_end_last":"2018-10-22T13:00:00-04:00","gmt_time_start":"2018-10-22 16:00:00","gmt_time_end":"2018-10-22 17:00:00","gmt_time_end_last":"2018-10-22 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"611934":{"#nid":"611934","#data":{"type":"event","title":"ARC Colloquium: Will Perkins (UIC)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EWill Perkins\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, November 5, 2018\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 East \u0026ndash; 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003EAlgorithmic Pirogov-Sinai theory\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u0026nbsp; We develop efficient algorithms to approximate the partition function and sample from the hard-core and Potts models on lattices at sufficiently low temperatures in the phase coexistence regime. In contrast, the Glauber dynamics are known to take exponential time to mix in this regime.\u0026nbsp; Our algorithms are based on the cluster expansion and Pirogov-Sinai theory, classical tools from statistical physics for understanding phase transitions, as well as Barvinok\u0026#39;s approach to polynomial approximation.\u0026nbsp; Joint work with Tyler Helmuth and Guus Regts.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022http:\/\/willperkins.org\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@cc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Algorithmic Pirogov-Sinai theory - Klaus 1116 East at 11 am"}],"uid":"27544","created_gmt":"2018-09-25 18:10:05","changed_gmt":"2018-09-25 18:10:05","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2018-11-05T11:00:00-05:00","event_time_end":"2018-11-05T12:00:00-05:00","event_time_end_last":"2018-11-05T12:00:00-05:00","gmt_time_start":"2018-11-05 16:00:00","gmt_time_end":"2018-11-05 17:00:00","gmt_time_end_last":"2018-11-05 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"607596":{"#nid":"607596","#data":{"type":"event","title":"ARC Colloquium: Tselil Schramm (Harvard\/MIT)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003ETselil Schramm\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, September 24, 2018\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMiRC Pettit 102 A\u0026amp;B\u0026nbsp; \u0026ndash; 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003E(Nearly) Efficient Algorithms for the\u0026nbsp;Graph\u0026nbsp;Matching\u0026nbsp;Problem in Correlated Random\u0026nbsp;Graphs\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u0026nbsp; The\u0026nbsp;Graph\u0026nbsp;Matching\u0026nbsp;problem is a robust version of the\u0026nbsp;Graph\u0026nbsp;Isomorphism problem: given two not-necessarily-isomorphic\u0026nbsp;graphs, the goal is to find a permutation of the vertices which maximizes the number of common edges. We study a popular average-case variant; we deviate from the common heuristic strategy and give the first quasi-polynomial time algorithm, where previously only sub-exponential time algorithms were known.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EBased on joint work with Boaz Barak, Chi-Ning Chou, Zhixian Lei, and Yueqi Sheng.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022http:\/\/tselilschramm.org\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@cc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"(Nearly) Efficient Algorithms for the Graph Matching Problem in Correlated Random Graphs - MiRC Pettit 102 A\u0026B at 11 am"}],"uid":"27544","created_gmt":"2018-07-10 14:01:41","changed_gmt":"2018-09-17 11:50:28","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2018-09-24T12:00:00-04:00","event_time_end":"2018-09-24T13:00:00-04:00","event_time_end_last":"2018-09-24T13:00:00-04:00","gmt_time_start":"2018-09-24 16:00:00","gmt_time_end":"2018-09-24 17:00:00","gmt_time_end_last":"2018-09-24 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"604923":{"#nid":"604923","#data":{"type":"event","title":"ARC Colloquium: Lap Chi Lau (Waterloo)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003ELap Chi Lau\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, October 15, 2018\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 East \u0026ndash; 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003EThe Paulsen problem, continuous operator scaling, and smoothed analysis\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u0026nbsp; The\u0026nbsp;Paulsen\u0026nbsp;problem is a basic open problem in operator theory.\u0026nbsp; We define\u0026nbsp;a continuous version of the operator scaling algorithm to solve this problem.\u0026nbsp; A key step is to show that the continuous operator scaling algorithm converges faster in a perturbed input. To this end, we develop some new techniques in lower bounding the operator capacity, a concept introduced by Gurvits to analyze the operator scaling algorithm.\u0026nbsp; The talk will be self-contained.\u0026nbsp; \u0026nbsp;Joint work with Tsz Chiu Kwok, Yin Tat Lee, and Akshay Ramachandran.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/cs.uwaterloo.ca\/~lapchi\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@cc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"The Paulsen problem, continuous operator scaling, and smoothed analysis - Klaus 1116E at 11 am"}],"uid":"27544","created_gmt":"2018-04-10 19:11:27","changed_gmt":"2018-09-14 13:26:48","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2018-10-15T12:00:00-04:00","event_time_end":"2018-10-15T13:00:00-04:00","event_time_end_last":"2018-10-15T13:00:00-04:00","gmt_time_start":"2018-10-15 16:00:00","gmt_time_end":"2018-10-15 17:00:00","gmt_time_end_last":"2018-10-15 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"609429":{"#nid":"609429","#data":{"type":"event","title":"ARC Colloquium: Anand Louis (Indian Inst. of Science)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAnand Louis (Indian Inst. of Science)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, September 10, 2018\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 East \u0026ndash; 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003EOn the complexity of clustering problems\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u0026nbsp; Euclidean k-means clustering, a problem having numerous applications, is NP-hard in the worst case but often solved efficiently in practice using simple heuristics. A quest for understanding the properties of real-world data sets that allow efficient clustering has lead to the notion of the perturbation resilience. In the first part of the talk, I\u0026#39;ll describe an algorithm to recover the optimal k-means clustering in perturbation resilient instances.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIn some cases, clustering with the k-means objective may result in a few clusters of very large cost and many clusters of small cost. This can be undesirable when we have a budget constraint on the cost of each cluster. Motivated by this, we study the \u0026quot;min-max k-means\u0026quot; clustering objective. In the second part of the talk, I\u0026#39;ll show approximation algorithms for the min-max k-means problem.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EBased on joint works with Amit Deshpande and Apoorv Vikram Singh.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/drona.csa.iisc.ac.in\/~anand\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@cc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"On the complexity of clustering problems - Klaus 1116E at 11 am"}],"uid":"27544","created_gmt":"2018-08-08 14:00:43","changed_gmt":"2018-08-31 16:39:56","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2018-09-10T12:00:00-04:00","event_time_end":"2018-09-10T13:00:00-04:00","event_time_end_last":"2018-09-10T13:00:00-04:00","gmt_time_start":"2018-09-10 16:00:00","gmt_time_end":"2018-09-10 17:00:00","gmt_time_end_last":"2018-09-10 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"604927":{"#nid":"604927","#data":{"type":"event","title":"ARC Colloquium:  Nima Anari (Stanford)","body":[{"value":"\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003ENima Anari\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EMonday, April 30, 2018\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 East \u0026ndash; Noon\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cbr \/\u003E\r\n\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003EEntropy, Log-Concavity, and a Deterministic Approximation Algorithm for Counting Bases of Matroids\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u0026nbsp; We give a deterministic 2^O(rank) approximation algorithm to count the number of bases of a given matroid and the number of common bases of any two matroids. Based on a lower bound of Azar et al., this is almost the best possible result assuming oracle access to independent sets of matroids.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThere are two main ingredients in our result: For the first ingredient, we build upon recent results of Huh et al. and Adiprasito et al. on combinatorial hodge theory to derive a connection between matroids and log-concave polynomials. We expect that several new applications in approximation algorithms will be derived from this connection in future. Formally, we prove that the multivariate generating polynomial of the bases of any matroid is log-concave as a function over the positive orthant. For the second ingredient, we use a general framework for approximate counting in discrete problems, based on convex optimization and sub-additivity of the entropy. For matroids, we prove that an approximate super-additivity of the entropy holds, yielding an approximation algorithm, by relying on log-concavity of the corresponding polynomials.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EJoint work with Shayan Oveis Gharan and Cynthia Vinzant.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/nimaanari.com\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@cc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Entropy, Log-Concavity, and a Deterministic Approximation Algorithm for Counting Bases of Matroids - Klaus 1116E at 11 am"}],"uid":"27544","created_gmt":"2018-04-10 19:32:13","changed_gmt":"2018-04-24 18:15:29","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2018-04-30T13:00:00-04:00","event_time_end":"2018-04-30T14:00:00-04:00","event_time_end_last":"2018-04-30T14:00:00-04:00","gmt_time_start":"2018-04-30 17:00:00","gmt_time_end":"2018-04-30 18:00:00","gmt_time_end_last":"2018-04-30 18:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"601434":{"#nid":"601434","#data":{"type":"event","title":"ARC Colloquium:  Alexandre Stauffer (Bath)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlexandre Stauffer\u0026nbsp;(Bath)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, April 23, 2018\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 East - 11am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u0026nbsp; Competition in randomly growing processes\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003EWe consider random growth processes that compete for space over time.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThis is by now a classical topic in probability theory. The usual situation is that when the two processes have different speeds of growth, then one of the processes wins against the other.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIt is quite rare to find natural models where both processes coexist forever.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIn this talk I will discuss a random growth model, which we introduced as a tool to studying a famous model of dendritic growth from physics.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThis growth model can also be regarded as a model for blocking the spread of fake news in a network.\u0026nbsp;\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EWe will discuss the behavior of this processes, its phase transition and the occurrence of coexistence.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThis is based on joint works with Elisabetta Candellero (Warwick) and Vladas Sidoravicius (NYU Shanghai).\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E--------------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/sites.google.com\/site\/alexandrestauffer\/\u0022\u003ESpeaker\u0026#39;s webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@cc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Competition in randomly growing processes - Klaus 1116E at 11am"}],"uid":"32895","created_gmt":"2018-01-26 19:30:59","changed_gmt":"2018-04-16 19:19:34","author":"Eric Vigoda","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2018-04-23T12:00:00-04:00","event_time_end":"2018-04-23T13:00:00-04:00","event_time_end_last":"2018-04-23T13:00:00-04:00","gmt_time_start":"2018-04-23 16:00:00","gmt_time_end":"2018-04-23 17:00:00","gmt_time_end_last":"2018-04-23 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"603173":{"#nid":"603173","#data":{"type":"event","title":"ARC Colloquium:  Yin Tat Lee (UW)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EYin Tat Lee\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EFriday, March 16, 2018\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMiRC Pettit Rm 102A\u0026amp;B \u0026ndash; 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003El_p regression beyond self-concordance\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u0026nbsp; We consider the problem of linear regression where the l_2 norm loss (i.e., the usual least squares loss) is replaced by the l_p norm. We show how to solve such problems up to machine precision in O*(n^|1\/2\u0026minus;1\/p|) (dense) matrix-vector products and O*(1) matrix inversions, or alternatively in O*(n^|1\/2\u0026minus;1\/p|) calls to a (sparse) linear system solver. This improves the state of the art for any p not in {1,2,inf}. Furthermore we also propose a randomized algorithm solving such problems in input sparsity time, i.e., O*(Z+poly(d)) where Z is the size of the input and d is the number of variables. Such a result was only known for p=2. Finally we prove that these results lie outside the scope of the Nesterov-Nemirovski\u0026#39;s theory of interior point methods by showing that any symmetric self-concordant barrier on the l_p unit ball has self-concordance parameter \u0026Omega;~(n).\u003C\/p\u003E\r\n\r\n\u003Cp\u003EJoint work with S\u0026eacute;bastien Bubeck, Michael B. Cohen, Yin Tat Lee, Yuanzhi Li\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022http:\/\/yintat.com\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@cc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"l_p regression beyond self-concordance - MiRC Pettit Rm 102A\u0026B at 11:00am"}],"uid":"27544","created_gmt":"2018-03-02 13:19:43","changed_gmt":"2018-03-02 13:22:39","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2018-03-16T12:00:00-04:00","event_time_end":"2018-03-16T13:00:00-04:00","event_time_end_last":"2018-03-16T13:00:00-04:00","gmt_time_start":"2018-03-16 16:00:00","gmt_time_end":"2018-03-16 17:00:00","gmt_time_end_last":"2018-03-16 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"601435":{"#nid":"601435","#data":{"type":"event","title":"ARC-TRIAD Colloquium:  Piotr Indyk (MIT)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC) and TRIAD\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EPiotr Indyk\u0026nbsp;(MIT)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, March 5, 2018\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 East - 11am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u0026nbsp; \u0026nbsp;\u0026quot;Below P vs. NP: Conditional Quadratic-Time Hardness for Big Data Problems\u0026quot;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003E \u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThe theory of NP-hardness has been very successful in identifying problems that are unlikely to have general purpose polynomial time algorithms. However, many other important problems do have polynomial time algorithms, but large exponents in their time bounds can make them run for days, weeks or more. For example, quadratic time algorithms, although practical on moderately sized inputs, can become inefficient on problems that involve gigabytes or more of data. Although for many problems no subquadratic time algorithms are known, evidence of quadratic-time hardness has remained elusive.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIn this talk, I will give an overview of recent research that aims to remedy this situation. In particular, I will describe hardness results for problems in string processing (e.g., edit distance computation or regular expression matching) and machine learning (e.g., support vector machines or batch gradient computation in neural networks). All of them have polynomial time algorithms, but despite an extensive amount of research, no near-linear time algorithms have been found for many variants of these problems. I will show that, under a natural complexity-theoretic conjecture, such algorithms do not exist. I will also describe how this framework has led to the development of new algorithms.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E--------------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/people.csail.mit.edu\/indyk\/\u0022\u003ESpeaker\u0026#39;s webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@cc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"\u0022Below P vs. NP: Conditional Quadratic-Time Hardness for Big Data Problems\u0022 - Klaus 1116E at 11am"}],"uid":"32895","created_gmt":"2018-01-26 19:32:00","changed_gmt":"2018-02-27 14:01:59","author":"Eric Vigoda","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2018-03-05T11:00:00-05:00","event_time_end":"2018-03-05T12:00:00-05:00","event_time_end_last":"2018-03-05T12:00:00-05:00","gmt_time_start":"2018-03-05 16:00:00","gmt_time_end":"2018-03-05 17:00:00","gmt_time_end_last":"2018-03-05 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"602428":{"#nid":"602428","#data":{"type":"event","title":"ARC Colloquium: Sanjeev Arora (Princeton\/IAS)","body":[{"value":"\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003ESanjeev Arora\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EPrinceton University and Institute for Advanced Study\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EFriday, February 23, 2018\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EKlaus 2447 (classroom) at 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003EToward theoretical understanding of deep learning\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u0026nbsp; This talk will be a survey of ongoing efforts to develop better theoretical understanding of deep learning, from expressiveness to optimization to generalization theory.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/www.cs.princeton.edu\/~arora\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@cc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Toward theoretical understanding of deep learning - Klaus 2447 (classroom) at 11am"}],"uid":"32895","created_gmt":"2018-02-15 17:53:57","changed_gmt":"2018-02-20 14:16:15","author":"Eric Vigoda","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2018-02-23T11:00:00-05:00","event_time_end":"2018-02-23T12:00:00-05:00","event_time_end_last":"2018-02-23T12:00:00-05:00","gmt_time_start":"2018-02-23 16:00:00","gmt_time_end":"2018-02-23 17:00:00","gmt_time_end_last":"2018-02-23 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"601432":{"#nid":"601432","#data":{"type":"event","title":"ARC Colloquium:  Xiaorui Sun (Microsoft)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EXiaorui Sun\u0026nbsp;(Microsoft Research)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, March 12, 2018\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 East - 11am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u0026nbsp;\u0026nbsp; The Query Complexity of Graph Isomorphism: Bypassing Distribution Testing Lower Bounds\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003E \u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EWe study the edge query complexity of graph isomorphism in the property testing model for dense graphs. We give an algorithm that makes n^{1+o(1)} queries, improving on the previous best bound of O~(n^{5\/4}). Since the problem is known to require \\Omega(n) queries, our algorithm is optimal up to a subpolynomial factor.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EWhile trying to extend a known connection to distribution testing, discovered by Fischer and Matsliah (SICOMP 2008), one encounters a natural obstacle presented by sampling lower bounds such as the $\\Omega(n^{2\/3})$-sample lower bound for distribution closeness testing (Valiant, SICOMP 2011). In the context of graph isomorphism testing, these bounds lead to an $n^{1+\\Omega(1)}$ barrier for Fischer and Matsliah\u0026#39;s approach. We circumvent these limitations by exploiting a geometric representation of the connectivity of vertices. An approximate representation of similarities between vertices can be learned with a near-linear number of queries and allows relaxed versions of sampling and distribution testing problems to be solved more efficiently.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EJoint work with Krzysztof Onak\u003C\/p\u003E\r\n\r\n\u003Cp\u003E--------------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022http:\/\/www.cs.columbia.edu\/~xiaoruisun\/\u0022\u003ESpeaker\u0026#39;s webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@cc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":" The Query Complexity of Graph Isomorphism: Bypassing Distribution Testing Lower Bounds- Klaus 1116E at 11am"}],"uid":"32895","created_gmt":"2018-01-26 19:29:25","changed_gmt":"2018-02-16 21:10:52","author":"Eric Vigoda","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2018-03-12T12:00:00-04:00","event_time_end":"2018-03-12T13:00:00-04:00","event_time_end_last":"2018-03-12T13:00:00-04:00","gmt_time_start":"2018-03-12 16:00:00","gmt_time_end":"2018-03-12 17:00:00","gmt_time_end_last":"2018-03-12 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"602340":{"#nid":"602340","#data":{"type":"event","title":"ARC Colloquium:  Vivek Madan (UIUC)","body":[{"value":"\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EVivek Madan(UIUC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EMonday, February 19, 2018\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 East \u0026ndash; 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003EApproximating Multicut and the Demand graph\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u0026nbsp; The Multicut problem is a generalization of the classical $s-t$ cut problem to multiple pairs. Given an edge-weighted directed or undirected supply graph G=(V,E), and k source-sink pairs (s1,t1),\\dots,(sk,tk), the goal is to remove a minimum weight subset of edges in G such that all the given (si,ti) pairs are disconnected. Over the past 30 years, Multicut has attracted significant attention in approximation algorithms, and a variety of results have been obtained for general and special classes of supply graphs. Motivated by new applications, I study Multicut with a focus on the demand graph (graph with an edge set {(si,ti) \\mid i \\in [k]}). We obtain several new approximability and inapproximability results based on a labeling viewpoint of the problem.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E1.\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; Approximation algorithms: We present a unified 2-approximation algorithm for undirected multicut problem for tK2-free demand graphs when t is a fixed constant. For directed multiway cut we significantly simplify the 2-approximation algorithm of Naor and Zosin from twenty years ago; our rounding strategy yields a constant factor for much more general classes of demand graphs. For the problem of linear-k-cut (a special case of directed multicut which motivated this work), we show some initial results and prove a tight \\sqrt{2}-approximation algorithm when k=3.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E2.\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; Hardness of approximation: We prove that for a class of demand graphs, undirected multicut admits a constant factor approximation algorithm iff the class is tK2-free for some constant t. For directed multicut, we prove that assuming the Unique Games Conjecture (UGC), hardness of approximation matches the flow-cut gap for any fixed bi-partite demand graph. As a consequence, we prove that for any fixed k \\ge 2, there is no (k-eps) approximation algorithm for Multicut with k pairs, assuming UGC.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022http:\/\/vmadan2.web.engr.illinois.edu\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@cc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Approximating Multicut and the Demand Graph - Klaus 1116 East at 11:00am"}],"uid":"27544","created_gmt":"2018-02-14 12:53:08","changed_gmt":"2018-02-14 20:37:21","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2018-02-19T11:00:00-05:00","event_time_end":"2018-02-19T12:00:00-05:00","event_time_end_last":"2018-02-19T12:00:00-05:00","gmt_time_start":"2018-02-19 16:00:00","gmt_time_end":"2018-02-19 17:00:00","gmt_time_end_last":"2018-02-19 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"601408":{"#nid":"601408","#data":{"type":"event","title":"ARC Colloquium:  Greg Bodwin (MIT)","body":[{"value":"\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EGreg Bodwin\u0026nbsp;(MIT)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EFriday, February 9, 2018\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003ESkiles 005 - 1pm\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ENote the non-standard date\/time\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u0026nbsp; \u0026nbsp; The Distance Oracle Hierarchy\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003E \u0026nbsp; A lot of well-studied problems in CS Theory are about making \u0026ldquo;sketches\u0026rdquo; of graphs that occupy much less space than the graph itself, but where the shortest path distances of the graph can still be approximately recovered from the sketch. For example, in the literature on Spanners, we seek a sparse subgraph whose distance metric approximates that of the original graph. In Emulator literature, we relax the requirement that the approximating graph is a subgraph. Most generally, in Distance Oracles, the sketch can be an arbitrary data structure, so long as it can approximately answer queries about the pairwise distance between nodes in the original graph.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EResearch on these objects typically focuses on optimizing the worst-case tradeoff between the quality of the approximation and the amount of space that the sketch occupies. In this talk, we will survey a recent leap in understanding about this tradeoff, overturning the conventional wisdom on the problem. Specifically, the tradeoff is not smooth, but rather it follows a new discrete hierarchy in which the quality of the approximation that can be obtained jumps considerably at certain predictable size thresholds. The proof is graph-theoretic and relies on building large families of graphs with large discrepancies in their metrics.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E--------------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/sites.google.com\/site\/gregbodwin\/\u0022\u003ESpeaker\u0026#39;s webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@cc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"The Distance Oracle Hierarchy - Skiles 005 at 1pm "}],"uid":"32895","created_gmt":"2018-01-26 16:58:52","changed_gmt":"2018-01-30 19:37:55","author":"Eric Vigoda","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2018-02-09T13:00:00-05:00","event_time_end":"2018-02-09T14:00:00-05:00","event_time_end_last":"2018-02-09T14:00:00-05:00","gmt_time_start":"2018-02-09 18:00:00","gmt_time_end":"2018-02-09 19:00:00","gmt_time_end_last":"2018-02-09 19:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"601198":{"#nid":"601198","#data":{"type":"event","title":"ARC Colloquium: Aaron Schild (Berkeley)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAaron Schild (Berkeley)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, February 12, 2018\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 East \u0026ndash; 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003EAn almost-linear time algorithm for uniform random spanning tree generation\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u0026nbsp; We give an $m^{1+o(1)}\\beta^{o(1)}$-time algorithm for generating uniformly random spanning trees in weighted graphs with max-to-min weight ratio $\\beta$. In the process, we illustrate how fundamental tradeoffs in graph partitioning can be overcome by eliminating vertices from a graph using Schur complements of the associated Laplacian matrix.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EOur starting point is the Aldous-Broder algorithm, which samples a random spanning tree using a random walk. As in prior work, we use fast Laplacian linear system solvers to shortcut the random walk from a vertex $v$ to the boundary of a set of vertices assigned to $v$ called a \u0026quot;shortcutter.\u0026quot; We depart from prior work by introducing a new way of employing Laplacian solvers to shortcut the walk. To bound the amount of shortcutting work, we show that most random walk steps occur far away from an unvisited vertex. We apply this observation by charging uses of a shortcutter $S$ to random walk steps in the Schur complement obtained by eliminating all vertices in $S$ that are not assigned to it.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/people.eecs.berkeley.edu\/~aschild\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@cc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"An almost-linear time algorithm for uniform random spanning tree generation - Klaus 1116 East at 11am"}],"uid":"27544","created_gmt":"2018-01-23 15:53:40","changed_gmt":"2018-01-29 13:36:28","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2018-02-12T11:00:00-05:00","event_time_end":"2018-02-12T12:00:00-05:00","event_time_end_last":"2018-02-12T12:00:00-05:00","gmt_time_start":"2018-02-12 16:00:00","gmt_time_end":"2018-02-12 17:00:00","gmt_time_end_last":"2018-02-12 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"601407":{"#nid":"601407","#data":{"type":"event","title":"ARC Colloquium: Di Wang (Berkeley\/GaTech)","body":[{"value":"\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EDi Wang\u0026nbsp;(UC Berkeley\/Georgia Tech)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EMonday, February 5, 2018\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 East\u0026nbsp;- 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u0026nbsp; \u0026nbsp;Capacity Releasing Diffusion for Speed and Locality\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003E \u0026nbsp; Diffusion and related random walk procedures on graphs are of central importance in many areas of machine learning, data analysis, and algorithm design. Because they spread mass agnostically at each step in an iterative manner, they can sometimes spread mass \u0026ldquo;too aggressively,\u0026rdquo; thereby failing to find the \u0026ldquo;right\u0026rdquo; clusters. We introduce a novel Capacity Releasing Diffusion (CRD) Process, which is both faster and stays more local than the classical probability mass diffusion.\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\nThe CRD Process follows a carefully-constructed push-relabel rule, using techniques that are well-known from flow-based graph algorithms. While \ufb02ow and probability mass diffusion (or more generally, spectral methods) have a long history of competing to provide good graph decomposition, local methods are predominantly based on diffusion. Our CRD Process is the \ufb01rst primarily \ufb02ow-based local method for locating low conductance cuts, and it has exhibited improved theoretical and empirical behavior over classical di\ufb00usion methods, e.g. PageRank.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E--------------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@cc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Capacity Releasing Diffusion for Speed and Locality - Klaus 1116E at 11am"}],"uid":"32895","created_gmt":"2018-01-26 16:49:55","changed_gmt":"2018-01-26 19:37:42","author":"Eric Vigoda","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2018-02-05T11:00:00-05:00","event_time_end":"2018-02-05T12:00:00-05:00","event_time_end_last":"2018-02-05T12:00:00-05:00","gmt_time_start":"2018-02-05 16:00:00","gmt_time_end":"2018-02-05 17:00:00","gmt_time_end_last":"2018-02-05 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"600861":{"#nid":"600861","#data":{"type":"event","title":"ARC-TRIAD Seminar - Yan Shuo Tan (Michigan)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EARC-TRIAD\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EYan Shuo Tan (Michigan)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, January 22, 2018\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EPettit Microelectonics Bldg. \u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EPettit Rm 102A  -  2:00 pm\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003EEfficient algorithms for phase retrieval in high dimensions\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u0026nbsp; Mathematical phase retrieval is the problem of solving systems of rank-1 quadratic equations. Over the last few years, there has been much interest in constructing algorithms with provable guarantees. Both theoretically and empirically, the most successful approaches have involved direct optimization of non-convex loss functions. In the first half of this talk, we will discuss how SGD for one of these loss functions provably results in (rapid) linear convergence with high probability. In the second half of the talk, we will discuss a semidefinite programming algorithm that simultaneously makes use of a sparsity prior on the solution vector, while overcoming possible model misspecification.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022http:\/\/www-personal.umich.edu\/~yanshuo\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@cc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Efficient algorithms for phase retrieval in high dimensions"}],"uid":"27544","created_gmt":"2018-01-16 17:22:12","changed_gmt":"2018-01-19 15:33:31","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2018-01-22T14:00:00-05:00","event_time_end":"2018-01-22T15:00:00-05:00","event_time_end_last":"2018-01-22T15:00:00-05:00","gmt_time_start":"2018-01-22 19:00:00","gmt_time_end":"2018-01-22 20:00:00","gmt_time_end_last":"2018-01-22 20:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"600607":{"#nid":"600607","#data":{"type":"event","title":"ARC-TRIAD Seminar - Cong Han Lim (Wisconsin)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EARC-TRIAD\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003ECong Han Lim (Wisconsin)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EWednesday, January 17, 2018\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EGroseclose 402 - 10:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003ETowards Large-Scale Nonconvex\/Stochastic Discrete Optimization\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u0026nbsp; Modern data analytics is powered by scalable mathematical optimization methods. For decision-making, we want to be able to solve large-scale mathematical problems that include discrete choices or structures. These can already be very challenging to solve exactly even when the objective and feasible region are convex. We want to be able to model more general concepts that naturally lead to huge or nonconvex formulations, such as robustness to uncertainty, economic ideas like economies of scale, and physical concepts in engineering applications such as power systems and water network design.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;In this talk, I will present techniques for handling two such families of problems. I will demonstrate a new class of cutting planes for mixed-integer programs with separable concave costs and show that they can be combined with existing cuts for canonical mixed-integer linear sets. For stochastic mixed-integer programs, I will describe a new subgradient method for solving the dual decomposition that parallelizes significantly better than traditional subgradient on modern distributed and multi-core computer architectures. I will conclude by discussing some future directions in machine learning and (stochastic) mixed-integer programming.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/limconghan.github.io\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@cc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Towards Large-Scale Nonconvex\/Stochastic Discrete Optimization"}],"uid":"27544","created_gmt":"2018-01-10 13:32:13","changed_gmt":"2018-01-12 13:35:03","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2018-01-17T10:00:00-05:00","event_time_end":"2018-01-17T11:00:00-05:00","event_time_end_last":"2018-01-17T11:00:00-05:00","gmt_time_start":"2018-01-17 15:00:00","gmt_time_end":"2018-01-17 16:00:00","gmt_time_end_last":"2018-01-17 16:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"597635":{"#nid":"597635","#data":{"type":"event","title":"ARC Colloquium: Scott Aaronson (UT Austin)","body":[{"value":"\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EScott Aaronson (UT Austin)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EMonday, December 4, 2017\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 East \u0026amp; West - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u0026nbsp; Black Holes, Firewalls, and the Limits of Quantum Computers\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003EQuantum computers are proposed devices that would exploit quantum mechanics to solve certain specific problems dramatically faster than we know how to solve them with today\u0026#39;s computers.\u0026nbsp; In the popular press, quantum computers are often presented, not just as an exciting frontier of science and technology (which they are), but as magic devices that would work by simply trying every possible solution in parallel.\u0026nbsp; However, research over the past 25 years has revealed that the truth is much more subtle and problem-dependent: for some types of problems, quantum computers would offer only modest speedups or no speedups at all.\u0026nbsp; These limitations are entirely separate from the practical difficulties of building quantum computers (such as \u0026quot;decoherence\u0026quot;), and apply even to the fully error-corrected quantum computers we hope will be built in the future.\u0026nbsp; In this talk, I\u0026#39;ll give a crash course on what computer science has learned about both the capabilities and the limitations of quantum computers.\u0026nbsp; Then, in a final section, I\u0026#39;ll describe a remarkable and unexpected connection -- made just within the last five years -- where the conjectured limitations of quantum computers have been applied to issues in fundamental physics.\u0026nbsp; These include Hawking\u0026#39;s black-hole information puzzle (in its modern incarnation as the \u0026quot;firewall paradox\u0026quot;), and understanding the growth of wormholes in the so-called gauge\/gravity duality that emerged from string theory.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EBio:\u0026nbsp; \u003C\/strong\u003EScott Aaronson is David J. Bruton Centennial Professor of Computer Science at the University of Texas at Austin.\u0026nbsp; He received his bachelor\u0026#39;s from Cornell University and his PhD from UC Berkeley, and did postdoctoral fellowships at the Institute for Advanced Study as well as the University of Waterloo.\u0026nbsp; Before coming to UT Austin, he spent nine years as a professor in Electrical Engineering and Computer Science at MIT.\u0026nbsp; Aaronson\u0026#39;s research in theoretical computer science has focused mainly on the capabilities and limits of quantum computers.\u0026nbsp; His first book, Quantum Computing Since Democritus, was published in 2013 by Cambridge University Press.\u0026nbsp; He\u0026rsquo;s received the National Science Foundation\u0026rsquo;s Alan T. Waterman Award, the United States PECASE Award, the Vannevar Bush Fellowship, and MIT\u0026#39;s Junior Bose Award for Excellence in Teaching.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E--------------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/www.scottaaronson.com\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@cc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Black Holes, Firewalls, and the Limits of Quantum Computers Scott Aaronson (UT Austin) - Klaus 1116 East \u0026 West at 11am"}],"uid":"27544","created_gmt":"2017-10-19 19:27:23","changed_gmt":"2017-11-28 19:13:56","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2017-12-04T11:00:00-05:00","event_time_end":"2017-12-04T12:00:00-05:00","event_time_end_last":"2017-12-04T12:00:00-05:00","gmt_time_start":"2017-12-04 16:00:00","gmt_time_end":"2017-12-04 17:00:00","gmt_time_end_last":"2017-12-04 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"598579":{"#nid":"598579","#data":{"type":"event","title":"ACO-ARC Seminar: Vijay Vazirani (UC Irvine) ","body":[{"value":"\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EACO-ARC Seminar\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EVijay Vazirani (UC Irvine)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EThursday, November 16, 2017\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003ESkiles 005,\u0026nbsp;1:30 pm\u003C\/strong\u003E\u003Cbr \/\u003E\r\n\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle: \u0026nbsp;\u003C\/strong\u003E\u0026nbsp;Planar Graph Maximum Matching is in NC\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003EIs matching in NC, i.e., is there a deterministic fast parallel algorithm for it? This has been an outstanding open question in TCS for over three decades, ever since the discovery of Random NC matching algorithms. Within this question, the case of planar graphs has remained an enigma: On the one hand, counting the number of perfect matchings is far harder than finding one (the former is #P-complete and the latter is in P),\u0026nbsp; and on the other, for planar graphs, counting has long been known to be in NC whereas finding one has resisted a solution!\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThe case of bipartite planar graphs was solved by Miller and Naor in 1989 via a flow-based algorithm.\u0026nbsp; In 2000, Mahajan and Varadarajan gave an elegant way of using counting matchings to finding one, hence giving a different NC algorithm.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EHowever, non-bipartite planar graphs still didn\u0026#39;t yield: the stumbling block being odd tight cuts.\u0026nbsp; Interestingly enough, these are also a key to the solution: a balanced odd tight cut leads to a straight-forward divide and conquer NC algorithm. The remaining task is to find such a cut in NC. This requires several algorithmic ideas, such as finding a point in the interior of the minimum weight face of the perfect matching polytope and uncrossing odd tight cuts.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EJoint work with Nima Anari.\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Planar Graph Maximum Matching is in NC (Skiles 005 at 1:30pm)"}],"uid":"32895","created_gmt":"2017-11-09 13:46:06","changed_gmt":"2017-11-09 14:12:45","author":"Eric Vigoda","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2017-11-16T13:30:00-05:00","event_time_end":"2017-11-16T14:30:00-05:00","event_time_end_last":"2017-11-16T14:30:00-05:00","gmt_time_start":"2017-11-16 18:30:00","gmt_time_end":"2017-11-16 19:30:00","gmt_time_end_last":"2017-11-16 19:30:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"597633":{"#nid":"597633","#data":{"type":"event","title":"ARC Colloquium: Jonathan Hermon (Cambridge)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EJonathan Hermon (Cambridge)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, November 27, 2017\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 East - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u0026nbsp; A characterization of $L_p$ mixing, cutoff and hypercontractivity via maximal inequalities and hitting times.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003E(joint work with Yuval Peres): There are several works characterizing the total-variation mixing time of a reversible Markov chain in term of natural probabilistic concepts such as stopping times and hitting times. In contrast, there is no known analog for the uniform ($L_{\\infty}$) mixing time (UMT), (there is neither a sharp bound nor one possessing a probabilistic interpretation). We show that the UMT can be characterized up to a constant factor using hitting times distributions. We also derive a new extremal characterization of the Log-Sobolev constant, $c_{LS}$, as a weighted version of the spectral gap. This characterization yields a probabilistic interpretation of $c_{LS}$ in terms of a hitting time version of hypercontractivity. As applications, we (1) resolve a conjecture of Kozma by showing that the UMT is not robust under rough isometries (even in the bounded degree, unweighted setup), (2) show that for weighted nearest neighbor random walks on trees, the UMT is robust under bounded perturbations of the edge weights, and (3) Establish a general robustness result under addition of weighted self-loops.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E--------------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/www.stat.berkeley.edu\/~jonathan.hermon\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@cc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"A characterization of $L_p$ mixing, cutoff and hypercontractivity via maximal inequalities and hitting times (Klaus 1116 East at 11am)"}],"uid":"27544","created_gmt":"2017-10-19 19:21:58","changed_gmt":"2017-11-01 17:34:18","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2017-11-27T11:00:00-05:00","event_time_end":"2017-11-27T12:00:00-05:00","event_time_end_last":"2017-11-27T12:00:00-05:00","gmt_time_start":"2017-11-27 16:00:00","gmt_time_end":"2017-11-27 17:00:00","gmt_time_end_last":"2017-11-27 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"597631":{"#nid":"597631","#data":{"type":"event","title":"ARC Colloquium: Aviad Rubinstein (UC Berkeley)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAviad Rubinstein (UC Berkeley)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, November 6, 2017\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 East - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E Distributed PCP Theorems for Hardness of Approximation in P\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EWe present a new model of probabilistically checkable proof (PCP), which we call \u0026quot;Distributed PCP\u0026quot;:\u003C\/p\u003E\r\n\r\n\u003Cp\u003EA satisfying assignment (x in {0,1}^n) to a CNF formula is shared between two parties (Alice knows x_1, ... x_{n\/2}, and Bob knows x_{n\/2+1},...,x_n).\u003C\/p\u003E\r\n\r\n\u003Cp\u003ETheir goal is to jointly write a PCP for x, while exchanging little or no information.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EUsing our new framework, we obtain, for the first time, PCP-like reductions from the Strong Exponential Time Hypothesis (SETH) to approximation problems in P.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EBased in part on joint work with Amir Abboud and Ryan Williams.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E--------------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/people.eecs.berkeley.edu\/~aviad\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@cc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Distributed PCP Theorems for Hardness of Approximation in P (Klaus 1116 East at 11am)"}],"uid":"27544","created_gmt":"2017-10-19 19:08:58","changed_gmt":"2017-11-01 17:23:31","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2017-11-06T11:00:00-05:00","event_time_end":"2017-11-06T12:00:00-05:00","event_time_end_last":"2017-11-06T12:00:00-05:00","gmt_time_start":"2017-11-06 16:00:00","gmt_time_end":"2017-11-06 17:00:00","gmt_time_end_last":"2017-11-06 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"597444":{"#nid":"597444","#data":{"type":"event","title":"ARC 11 with Keynote by Robert Schapire","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ESchedule:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E10:00 \u0026ndash; 10:30\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; Talk \u0026ndash; \u003Cstrong\u003EJohn Wilmes\u003C\/strong\u003E (Georgia Tech)\u003C\/p\u003E\r\n\r\n\u003Cp\u003E10:30 \u0026ndash; 11:00 \u0026nbsp;\u0026nbsp;\u0026nbsp; Talk \u0026ndash; \u003Cstrong\u003EAntonio Blanca\u003C\/strong\u003E (Georgia Tech)\u003C\/p\u003E\r\n\r\n\u003Cp\u003E11:00 \u0026ndash; 12:00\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; Keynote by \u003Cstrong\u003ERobert Schapire \u003C\/strong\u003E(Microsoft Research NYC)\u003C\/p\u003E\r\n\r\n\u003Cp\u003ELunch in Klaus Atrium\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003E_________________\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EJohn Wilmes (Georgia Tech)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003EThe Complexity of Learning Neural Networks\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThe empirical successes of neural networks currently lack rigorous theoretical explanation. A first step might be to show that data generated by neural networks with a single hidden layer, smooth activation functions and benign input distributions can be learned efficiently. We demonstrate a surprisingly general lower bound. For inputs drawn from any logconcave distribution, we construct a family of functions that is hard to learn in the sense that any statistical query algorithm (including all known variants of stochastic gradient descent with any loss function, for any model architecture) needs an exponential number of queries even using tolerance inversely proportional to the input dimensionality. Moreover, this hard family of functions is realizable as neural networks using any activation function from a large family (including sigmoid and ReLU) with a small (sublinear in dimension) number of units in the single hidden layer, and whose output is a sum gate.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EJoint work with Le Song, Santosh Vempala, and Bo Xie.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E_________________\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAntonio Blanca (Georgia Tech)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003EDecay of correlations and non-local Markov chains\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u0026nbsp; In this talk we consider Markov chains for spin systems on the integer lattice graph Z^d. It has been well known since pioneering work from the early 1990\u0026rsquo;s that a certain decay of correlation property, known as strong spatial mixing (SSM), is a necessary and sufficient condition for fast mixing of the Gibbs sampler, where the state of a single vertex is updated in each step. In practice, non-local Markov chains are particularly popular from their potentially exponential speed-up, but these processes have largely resisted analysis. In this talk, we consider the effects of SSM on the rate of convergence to stationary of non-local Markov chains. We show that SSM implies fast mixing of several standard non-local chains, including general blocks dynamics, systematic scan dynamics and the Swendsen-Wang dynamics for the Ising\/Potts model. Our proofs use a variety of techniques for the analysis of Markov chains including coupling, functional analysis and linear algebra.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E_________________\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EKeynote Speaker\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ERobert Schapire, Microsoft Research (NYC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003EThe Contextual Bandits Problem:\u0026nbsp; Techniques for Learning to Make High-Reward Decisions\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003EWe consider how to learn through experience to make intelligent decisions.\u0026nbsp; In the generic setting, called the contextual bandits problem, the learner must repeatedly decide which action to take in response to an observed context, and is then permitted to observe the received reward, but only for the chosen action.\u0026nbsp; The goal is to learn to behave nearly as well as the best policy (or decision rule) in some possibly very large and rich space of candidate policies.\u0026nbsp; This talk will describe progress on developing general methods for this problem and some of its variants.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EBio:\u0026nbsp; \u003C\/strong\u003ERobert Schapire is a Principal Researcher at Microsoft Research in New York City.\u0026nbsp; He received his PhD from MIT in 1991.\u0026nbsp; After a short post-doc at Harvard, he joined the technical staff at AT\u0026amp;T Labs (formerly AT\u0026amp;T Bell Laboratories) in 1991.\u0026nbsp; In 2002, he became a Professor of Computer Science at Princeton University.\u0026nbsp; He joined Microsoft Research in 2014.\u0026nbsp; His awards include the 1991 ACM Doctoral Dissertation Award, the 2003 G\u0026ouml;del Prize, and the 2004 Kanelakkis Theory and Practice Award (both of the last two with Yoav Freund).\u0026nbsp; He is a fellow of the AAAI, and a member of both the National Academy of Engineering and the National Academy of Sciences.\u0026nbsp; His main research interest is in theoretical and applied machine learning, with particular focus on boosting, online learning, game theory, and maximum entropy.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThe Algorithms \u0026amp; Randomness Center presents ARC11 with Keynote speaker Robert Schapire of Microsoft Research (NYC), along with talks by John Wilmes(CS) and Antonio Blanca (CS)\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"The Contextual Bandits Problem: Techniques for Learning to Make High-Reward Decisions (Klaus 1116 E\u0026W at 11:00am)"}],"uid":"27544","created_gmt":"2017-10-16 16:24:38","changed_gmt":"2017-10-19 18:53:56","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2017-10-30T11:00:00-04:00","event_time_end":"2017-10-30T13:00:00-04:00","event_time_end_last":"2017-10-30T13:00:00-04:00","gmt_time_start":"2017-10-30 15:00:00","gmt_time_end":"2017-10-30 17:00:00","gmt_time_end_last":"2017-10-30 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"},{"id":"47223","name":"College of Computing"},{"id":"50875","name":"School of Computer Science"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"595514":{"#nid":"595514","#data":{"type":"event","title":"ARC Colloquium: Mike Molloy (Univ. of Toronto)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMike Molloy (Univ. of Toronto)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EFriday, October 20, 2017\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003ESkiles 005 - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u0026nbsp; \u003Ca href=\u0022https:\/\/arxiv.org\/abs\/1701.09133\u0022\u003EThe list chromatic number of graphs with small clique number\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EWe prove that every triangle-free graph with maximum degree $\\D$ has list chromatic number at most $(1+o(1))\\frac{\\D}{\\ln \\D}$. This matches the best-known bound for graphs of girth at least 5.\u0026nbsp; We also provide a new proof\u0026nbsp;that for any $r\\geq4$ every $K_r$-free graph has list-chromatic number at most $200r\\frac{\\D\\ln\\ln\\D}{\\ln\\D}$.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E--------------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022http:\/\/www.cs.toronto.edu\/~molloy\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/a\u003E\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003EClick here to subscribe to the seminar email list: arc-colloq@cc.gatech.edu \u003C\/a\u003E\u003C\/em\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"The list chromatic number of graphs with small clique number (Skiles 005 at 11:00 am)"}],"uid":"27544","created_gmt":"2017-09-05 19:39:37","changed_gmt":"2017-10-13 18:35:57","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2017-10-20T12:00:00-04:00","event_time_end":"2017-10-20T13:00:00-04:00","event_time_end_last":"2017-10-20T13:00:00-04:00","gmt_time_start":"2017-10-20 16:00:00","gmt_time_end":"2017-10-20 17:00:00","gmt_time_end_last":"2017-10-20 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"595655":{"#nid":"595655","#data":{"type":"event","title":"ARC Colloquium: Barna Saha (UMass Amherst)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EBarna Saha (UMass Amherst)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, October 23, 2017\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 East - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003E\u003Cem\u003ELanguage Ed\u003C\/em\u003E\u003Cem\u003Eit Distance, (min,+)-Matrix Multiplication \u0026amp; Beyond\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThe language edit distance is a significant generalization of two basic problems in computer science: parsing and string edit distance computation. Given any context free grammar, it computes the minimum number of insertions, deletions and substitutions required to convert a given input string into a valid member of the language. In 1972, Aho and Peterson gave a dynamic programming algorithm that solves this problem in time cubic in the string length. Despite its vast number of applications, in forty years there has been no improvement over this running time.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EComputing (min,+)-product of two n by n matrices in truly subcubic time is an outstanding open question, as it is equivalent to the famous All-Pairs-Shortest-Paths problem. Even when matrices have entries bounded in [1,n], obtaining a truly subcubic (min,+)-product algorithm will be a major breakthrough in computer science.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIn this presentation, I will explore the connection between these two problems which led us to develop the first truly subcubic algorithms for the following problems with improvements coming for each of these problems after several decades: (1) language edit distance, (2) RNA-folding-a basic computational biology problem and a special case of language edit distance computation, (3) stochastic grammar parsing\u0026mdash;fundamental to natural language processing, and (4) (min,+)-product of integer matrices with entries bounded in n^(3-\u0026omega;-c) where c \u0026gt;0 is any constant and, \u0026omega; is the exponent of the fast matrix multiplication, believed to be 2.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EBarna Saha received her Ph.D. from the University of Maryland College Park, and then spent a couple of years at the AT\u0026amp;T Shannon Labs as a senior researcher before joining UMass Amherst in 2014. Her research interests are in theoretical computer science specifically in algorithm design and analysis, and large scale data analytics. She is the recipient of NSF CAREER Award (2017), Google Faculty Award (2016), Yahoo ACE Award (2015), Simons-Berkeley Research Fellowship (2015), NSF CRII Award (2015), Dean\u0026#39;s Dissertation Award from UMD (2011), and the best paper award and finalists for best papers at VLDB 2009 and ICDE 2012 respectively.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E-----------------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/barnasaha.net\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@cc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Language Edit Distance, (min,+)-Matrix Multiplication \u0026 Beyond (Klaus 1116 East at 11am)"}],"uid":"27544","created_gmt":"2017-09-07 14:54:16","changed_gmt":"2017-10-13 11:55:18","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2017-10-23T12:00:00-04:00","event_time_end":"2017-10-23T13:00:00-04:00","event_time_end_last":"2017-10-23T13:00:00-04:00","gmt_time_start":"2017-10-23 16:00:00","gmt_time_end":"2017-10-23 17:00:00","gmt_time_end_last":"2017-10-23 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"595513":{"#nid":"595513","#data":{"type":"event","title":"ARC Colloquium: Reza Gheissari (NYU)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EReza Gheissari (NYU)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, October 2, 2017\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 East - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp;\u003C\/strong\u003E\u003Cem\u003EMixing Times of Critical 2D Potts Models\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThe Potts model is a generalization of the Ising model to $q\\geq 3$ states; on $\\mathbb Z^d$ it is an extensively studied model of statistical mechanics, known to exhibit a rich phase transition for $d=2$ at some $\\beta_c(q)$. Specifically, the Gibbs measure on $\\mathbb Z^2$ exhibits a sharp transition between a disordered regime when $\\beta\u0026lt;\\beta_c(q)$ and an ordered regime when $\\beta\u0026gt;\\beta_c(q)$. At $\\beta=\\beta_c(q)$, when $q\\leq 4$, the Potts model has a continuous phase transition and its scaling limit is believed to be conformally invariant; when $q\u0026gt;4$, the phase transition is discontinuous and the ordered and disordered phases coexist. \u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EI will discuss recent progress, joint with E. Lubetzky, in analyzing the time to equilibrium (mixing time) of natural Markov chains (e.g., heat-bath\/Metropolis) for the 2D Potts model, where the mixing time on an $n\\times n$ torus should transition from $O(\\log n)$ at high temperatures to exponential in $n$ at low temperatures, via a critical slowdown at $\\beta=\\beta_c$ of $n^z$ when $q\\leq 4$ and exponential in $n$ when $q\u0026gt;4$.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E--------------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022http:\/\/cims.nyu.edu\/~reza\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/a\u003E\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003EClick here to subscribe to the seminar email list: arc-colloq@cc.gatech.edu \u003C\/a\u003E\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Mixing Times of Critical 2D Potts Models (Klaus 1116 East at 11am)"}],"uid":"27544","created_gmt":"2017-09-05 19:20:34","changed_gmt":"2017-09-25 16:36:55","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2017-10-02T12:00:00-04:00","event_time_end":"2017-10-02T13:00:00-04:00","event_time_end_last":"2017-10-02T13:00:00-04:00","gmt_time_start":"2017-10-02 16:00:00","gmt_time_end":"2017-10-02 17:00:00","gmt_time_end_last":"2017-10-02 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:ftonge3@cc.gatech.edu\u0022\u003Eftonge3@cc.gatech.edu\u003C\/a\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"595434":{"#nid":"595434","#data":{"type":"event","title":"ARC Colloquium: Stefanie Jegelka (MIT)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EStefanie Jegelka (MIT)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, September 25, 2017\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003ECaddell Flex Space Rm 122\u0026nbsp; -\u0026nbsp; 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003E\u003Cem\u003EVariations of Submodularity and Diversity: from Robust Optimization to Markov Chains\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract\u003C\/strong\u003E:\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThe combinatorial concept of submodular set functions has proved to be a very useful discrete structure for optimization in machine learning and its applications. In this talk, I will show recent work on generalizations and specializations of this structure, and its connections to robustness and efficiency in machine learning.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EFirst, generalizations to integer and continuous functions lead to algorithms for solving a special class of nonconvex optimization problems. We show how, with further work, this generalization can be leveraged for introducing robustness to uncertainty in budget allocation and bipartite influence maximization problems. The resulting algorithm solves a nonconvex minimax game.\u003C\/p\u003E\r\n\r\n\u003Cp\u003ESecond, log-submodular discrete probability measures that induce diversity, repulsion and strong notions of negative dependence find applications from randomized matrix approximations and model sketching for large-scale learning to experiment design and interpretable unsupervised learning. But practical sampling methods have hitherto been lagging behind. I will outline how connections to real stable polynomials lead to fast-mixing Markov Chains for practical sampling and to solving an open problem posed by Avron and Boutsidis (2013).\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThis talk is based on joint work with Matthew Staib, Chengtao Li and Suvrit Sra.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EBio:\u0026nbsp; \u003C\/strong\u003EStefanie Jegelka is an X-Consortium Career Development Assistant Professor in the Department of EECS at MIT. She is a member of the Computer Science and AI Lab (CSAIL), the Center for Statistics and an affiliate of IDSS and ORC. Before joining MIT, she was a postdoctoral researcher at UC Berkeley, and obtained her PhD from ETH Zurich and the Max Planck Institute for Intelligent Systems. Stefanie has received an NSF CAREER Award, a DARPA Young Faculty Award, a Google research award, the German Pattern Recognition Award and a Best Paper Award at the International Conference for Machine Learning (ICML). Her research interests span the theory and practice of algorithmic machine learning.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E--------------------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022http:\/\/people.csail.mit.edu\/stefje\/\u0022\u003ESpeaker\u0026#39;s webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/a\u003E\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003EClick here to subscribe to the seminar email list: arc-colloq@cc.gatech.edu \u003C\/a\u003E\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Variations of Submodularity and Diversity: from Robust Optimization to Markov Chains (Caddell Flex Space Rm 122-126 at 11:00 am)"}],"uid":"27544","created_gmt":"2017-09-01 17:02:26","changed_gmt":"2017-09-13 20:23:23","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2017-09-25T12:00:00-04:00","event_time_end":"2017-09-25T13:00:00-04:00","event_time_end_last":"2017-09-25T13:00:00-04:00","gmt_time_start":"2017-09-25 16:00:00","gmt_time_end":"2017-09-25 17:00:00","gmt_time_end_last":"2017-09-25 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:ftonge3@cc.gatech.edu\u0022\u003Eftonge3@cc.gatech.edu\u003C\/a\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"595431":{"#nid":"595431","#data":{"type":"event","title":"ARC Colloquium: Ilias Diakonikolas (USC)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EIlias Diakonikolas (USC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, September 18, 2017\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 East - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003E\u003Cem\u003EStatistical Query Lower Bounds for High-Dimensional Unsupervised Learning\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EWe describe a general technique that yields the first Statistical Query lower bounds for a range of fundamental high-dimensional learning problems. Our main results are for the problems of (1) learning Gaussian mixture models, and (2) robust learning of a single Gaussian distribution. For these problems, we show a super-polynomial gap between the sample complexity and the computational complexity of any Statistical Query (SQ) algorithm for the problem. SQ algorithms are a class of algorithms that\u0026nbsp; are only allowed to query expectations of functions of the distribution rather than directly access samples. This class of algorithms is quite broad: a wide range of known algorithmic techniques in machine learning are known to be implementable using SQs.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EOur SQ lower bounds are attained via a unified moment-matching technique that is useful in other contexts. Our method yields tight lower bounds for a number of related unsupervised estimation problems, including robust covariance estimation in spectral norm, and robust sparse mean estimation. Finally, for the classical problem of robustly testing an unknown mean Gaussian, we show a sample complexity lower bound that scales linearly in the dimension. This matches the sample complexity of the corresponding robust learning problem and separates the sample complexity of robust testing from standard testing. This separation is surprising because such a gap does not exist for the corresponding learning problem.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E(Based on joint work with Daniel Kane (UCSD) and Alistair Stewart (USC).)\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E Ilias Diakonikolas is an Assistant Professor and Andrew and Erna Viterbi Early Career Chair in the Department of Computer Science at USC. He obtained a Diploma in electrical and computer engineering from the National Technical University of Athens and a Ph.D. in computer science from Columbia University where he was advised by Mihalis Yannakakis. Before moving to USC, he was a faculty member at the University of Edinburgh, and prior to that he was the Simons postdoctoral fellow in theoretical computer science at the University of California, Berkeley. His research is on the algorithmic foundations\u003C\/p\u003E\r\n\r\n\u003Cp\u003Eof massive data sets, in particular on designing efficient algorithms for fundamental problems in machine learning. He is a recipient of a Sloan Fellowship, an NSF Career Award, a Google Faculty Research Award, a Marie Curie Fellowship, the IBM Research Pat Goldberg Best Paper Award, and an honorable mention in the George Nicholson competition from the INFORMS society.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E------------------------------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022http:\/\/www.iliasdiakonikolas.org\/\u0022\u003ESpeaker\u0026#39;s webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/a\u003E\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003EClick here to subscribe to the seminar email list: arc-colloq@cc.gatech.edu \u003C\/a\u003E\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Statistical Query Lower Bounds for High-Dimensional Unsupervised Learning (Klaus 1116 East at 11am)"}],"uid":"27544","created_gmt":"2017-09-01 16:48:33","changed_gmt":"2017-09-13 19:39:35","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2017-09-18T12:00:00-04:00","event_time_end":"2017-09-18T13:00:00-04:00","event_time_end_last":"2017-09-18T13:00:00-04:00","gmt_time_start":"2017-09-18 16:00:00","gmt_time_end":"2017-09-18 17:00:00","gmt_time_end_last":"2017-09-18 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:ftonge3@cc.gatech.edu\u0022\u003Eftonge3@cc.gatech.edu\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"595529":{"#nid":"595529","#data":{"type":"event","title":"ARC Seminar: Andreas Galanis (Oxford)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAndreas Galanis (Oxford)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EThursday, September 21, 2017\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 West - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp;\u0026nbsp; \u003C\/strong\u003E\u003Cem\u003ERandom Walks on Small World Networks\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EWe study the mixing time of random walks on small-world networks modelled as follows: starting with the 2-dimensional periodic grid, each pair of vertices {u,v} with distance d\u0026gt;1 is added as a \u0026quot;long-range\u0026quot; edge with probability proportional to d^(-r), where r\u0026gt;=0 is a parameter of the model. Kleinberg studied a close variant of this network model and proved that the decentralised routing time is O((logn)^2) when r=2 and n^\u0026Omega;(1) when r\\neq 2. Here, we prove that the random walk also undergoes a phase transition at r=2, but in this case the phase transition is of a different form. We establish that the mixing time is \u0026Theta;(logn) for r\u0026lt;2, O((logn)^4) for r=2 and n^{\u0026Omega;(1)} for r\u0026gt;2.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EJoint work with Martin Dyer, Leslie Ann Goldberg, Mark Jerrum, and Eric Vigoda.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E--------------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022http:\/\/www.cs.ox.ac.uk\/people\/andreas.galanis\/myindex.html\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@cc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Random Walks on Small World Networks (Klaus 1116 East at 11am)"}],"uid":"27544","created_gmt":"2017-09-06 12:41:22","changed_gmt":"2017-09-13 19:15:32","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2017-09-21T12:00:00-04:00","event_time_end":"2017-09-21T13:00:00-04:00","event_time_end_last":"2017-09-21T13:00:00-04:00","gmt_time_start":"2017-09-21 16:00:00","gmt_time_end":"2017-09-21 17:00:00","gmt_time_end_last":"2017-09-21 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:ftonge3@cc.gatech.edu\u0022\u003Eftonge3@cc.gatech.edu\u003C\/a\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"593876":{"#nid":"593876","#data":{"type":"event","title":"ARC Colloquium: Deeparnab Chakrabarty (Dartmouth)","body":[{"value":"\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EDeeparnab Chakrabarty (Dartmouth)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EFriday, August\u0026nbsp;4, 2017\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 East - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp;\u003C\/strong\u003ESubmodular Function Minimization via Continuous Optimization\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract\u003C\/strong\u003E:\u003C\/p\u003E\r\n\r\n\u003Cp\u003ESubmodular functions are beautiful objects arising in many areas including computer science, probability, operations research, etc.\u0026nbsp; They are set functions defined over subsets of an n-element universe with the property that f(A) + f(B) is at least f(union of A and B) + f(intersection of A and B). One paradigmatic problem is that of submodular function minimization: find the set which minimizes f with only oracle access to f. Amazingly, this can be done in polynomial time.\u0026nbsp; Recently, continuous optimization techniques have given rise to fast algorithms for submodular function minimization (SFM).\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EA large part of the talk will be survey-ish, and time permitting I will talk about some recent results of mine in this line.\u0026nbsp; The new results are joint work with Prateek Jain, Pravesh Kothari, Yin Tat Lee, Aaron Sidford, and Sam Wong.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022http:\/\/www.cs.dartmouth.edu\/~deepc\/\u0022\u003ESpeaker\u0026#39;s webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/a\u003E\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003EClick here to subscribe to the seminar email list: arc-colloq@cc.gatech.edu \u003C\/a\u003E\u003C\/em\u003E\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Submodular Function Minimization via Continuous Optimization (Klaus 1116E at 11am)"}],"uid":"32895","created_gmt":"2017-08-01 14:06:32","changed_gmt":"2017-08-01 14:06:32","author":"Eric Vigoda","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2017-08-04T12:00:00-04:00","event_time_end":"2017-08-04T13:00:00-04:00","event_time_end_last":"2017-08-04T13:00:00-04:00","gmt_time_start":"2017-08-04 16:00:00","gmt_time_end":"2017-08-04 17:00:00","gmt_time_end_last":"2017-08-04 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"582459":{"#nid":"582459","#data":{"type":"event","title":"ARC Colloquium: Emmanuel Abbe (Princeton)","body":[{"value":"\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EEmmanuel Abbe (Princeton)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EMonday, April 10, 2017\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 East - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp;\u003C\/strong\u003EOld and new on the stochastic block model\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract\u003C\/strong\u003E:\u003Cbr \/\u003E\r\nWe will review the basic phase transition results for the stochastic block model, covering both the weak and exact recovery of the communities. Focus will be put on the general case. We will discuss in particular the proof of the physicists conjecture about achieving the Kesten-Stigum threshold efficiently for any number of communities, and crossing that threshold information-theoretically for four communities.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022http:\/\/www.ee.princeton.edu\/research\/eabbe\/?q=node\/1\u0022\u003ESpeaker\u0026#39;s webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/a\u003E\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003EClick here to subscribe to the seminar email list: arc-colloq@cc.gatech.edu \u003C\/a\u003E\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":" Old and new on the stochastic block model (Klaus 1116 E at 11am)"}],"uid":"27466","created_gmt":"2016-10-12 18:04:35","changed_gmt":"2017-04-17 16:14:05","author":"Dani Denton","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2017-04-10T12:00:00-04:00","event_time_end":"2017-04-10T13:00:00-04:00","event_time_end_last":"2017-04-10T13:00:00-04:00","gmt_time_start":"2017-04-10 16:00:00","gmt_time_end":"2017-04-10 17:00:00","gmt_time_end_last":"2017-04-10 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[{"id":"92341","name":"Algorithms and Randomness Center"},{"id":"4265","name":"ARC"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EEric Vigoda\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"586435":{"#nid":"586435","#data":{"type":"event","title":"ARC Colloquium: Philip Klein (Brown)","body":[{"value":"\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EPhilip N. Klein (Brown)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EMonday, March 27, 2017\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 East - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp;\u003C\/strong\u003EApproximation Schemes for Planar Graphs: A Survey of Methods\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract\u003C\/strong\u003E:\u003Cbr \/\u003E\r\nIn addressing an NP-hard problem in combinatorial optimization, one way to cope is to use an\u0026nbsp;\u003Cem\u003Eapproximation scheme\u003C\/em\u003E, an algorithm that, for any given\u0026nbsp;\u03f5\u0026gt;0, produces a solution whose value is within a\u0026nbsp;1+\u03f5\u0026nbsp;factor of optimal. For many problems on graphs, obtaining such accurate approximations is NP-hard if the input is allowed to be any graph but is tractable if the input graph is required to be planar.\u0026nbsp;\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\nResearch on polynomial-time approximation schemes for optimization problems in planar graphs goes back to the pioneering work of Lipton and Tarjan (1977) and Baker (1983). Since then, however, the scope of problems amenable to approximation has broadened considerably. In this talk I will outline some of the approaches used, especially those that have led to recent results.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ESpeaker\u0026#39;s Bio\u003C\/strong\u003E:\u003C\/p\u003E\r\n\r\n\u003Cp\u003EPhil Klein is Professor of Computer Science at Brown University.\u0026nbsp; He\u0026nbsp;received an A.B. in Applied Mathematics from Harvard and a Ph.D. in\u0026nbsp;Computer Science from MIT.\u0026nbsp; His research area is algorithms for\u0026nbsp;finding optimal and approximately optimal solutions to optimization\u0026nbsp;problems in graphs and networks.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EHe is an ACM Fellow, a recipient of the Presidential Young\u0026nbsp;Investigator Award, and a recipient of Brown University\u0026#39;s Philip\u0026nbsp;J. Bray Award for Excellence in Teaching in the Sciences.\u0026nbsp; He was the\u0026nbsp;SODA Program Committee Chair in 2017, and a Radcliffe Institute\u003Cbr \/\u003E\r\nFellow in 2016-2017.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/cs.brown.edu\/people\/klein\/\u0022\u003ESpeaker\u0026#39;s webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/a\u003E\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\n\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003EClick here to subscribe to the seminar email list: arc-colloq@cc.gatech.edu \u003C\/a\u003E\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Approximation Schemes for Planar Graphs: A Survey of Methods (Klaus 1116 E at 11am)"}],"uid":"32895","created_gmt":"2017-01-25 14:38:16","changed_gmt":"2017-04-17 16:13:02","author":"Eric Vigoda","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2017-03-27T12:00:00-04:00","event_time_end":"2017-03-27T13:00:00-04:00","event_time_end_last":"2017-03-27T13:00:00-04:00","gmt_time_start":"2017-03-27 16:00:00","gmt_time_end":"2017-03-27 17:00:00","gmt_time_end_last":"2017-03-27 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"590507":{"#nid":"590507","#data":{"type":"event","title":"ARC Colloquium: Michael Cohen (MIT)","body":[{"value":"\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align=\u0022center\u0022 \u003E\u003Cstrong\u003EMichael Cohen (MIT)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EMonday, May 1, 2017\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 East - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp;\u003C\/strong\u003ENew Algorithms for Matrix Scaling Problems via Second-order Methods and Generalized Laplacian System Solvers\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract\u003C\/strong\u003E:\u003Cbr \/\u003E\r\nIn this paper, we study matrix scaling and balancing, which are fundamental problems in scientific computing, with a long line of work on them that dates back to the 1960s. We provide algorithms for both these problems that, ignoring logarithmic factors involving the dimension of the input matrix and the size of its entries, both run in time m log(k) log^2(1\/eps) where eps is the amount of error we are willing to tolerate. Here, k represents the ratio between the largest and the smallest entries of the optimal scalings. This implies that our algorithms run in nearly-linear time whenever k is quasi-polynomial, which includes, in particular, the case of strictly positive matrices.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIn order to establish these results, we develop a new second-order optimization framework that enables us to treat both problems in a unified and principled manner. This framework identifies a certain generalization of linear system solving which we can use to efficiently minimize a broad class of functions, which we call second-order robust. We then show that in the context of the specific functions capturing matrix scaling and balancing, we can leverage and generalize the work on Laplacian system solving to make the algorithms obtained via this framework very efficient.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EWe also discuss an interior point method that runs in time, up to logarithmic factors, of m^{3\/2} log(1\/eps) for the case of matrix balancing and the doubly-stochastic variant of matrix scaling (with an additional log(log(k)) bound in a more general setting).\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EJoint work with Aleksander Madry, Dimitris Tsipras, and Adrian Vladu.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EArXiv posting:\u0026nbsp;\u003Ca href=\u0022https:\/\/arxiv.org\/abs\/1704.02310\u0022 target=\u0022_blank\u0022\u003Ehttps:\/\/arxiv.org\/abs\/1704.02310\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EA similar approach (but not using the generalization of Laplacian solvers and hence obtaining somewhat different results) was developed independently by Zeyuan Allen-Zhu, Yuanzhi Li, Rafael Oliveira, and Avi Wigderson:\u0026nbsp;\u003Ca href=\u0022https:\/\/arxiv.org\/abs\/1704.02315\u0022 target=\u0022_blank\u0022\u003Ehttps:\/\/arxiv.org\/abs\/1704.02315\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/scholar.google.com\/citations?user=t3kDJHQAAAAJ\u0026amp;hl=en\u0022\u003ESpeaker\u0026#39;s webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003EClick here to subscribe to the seminar email list: arc-colloq@cc.gatech.edu \u003C\/a\u003E\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"New Algorithms for Matrix Scaling Problems via Second-order Methods and Generalized Laplacian System Solvers (Klaus 1116E at 11am)"}],"uid":"32895","created_gmt":"2017-04-17 16:07:25","changed_gmt":"2017-04-17 16:10:47","author":"Eric Vigoda","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2017-05-01T12:00:00-04:00","event_time_end":"2017-05-01T13:00:00-04:00","event_time_end_last":"2017-05-01T13:00:00-04:00","gmt_time_start":"2017-05-01 16:00:00","gmt_time_end":"2017-05-01 17:00:00","gmt_time_end_last":"2017-05-01 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"202711":{"#nid":"202711","#data":{"type":"event","title":"ARC Colloquium: Ricardo Restrepo, Institute of Mathematics, Universidad de Antioquia","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E Frozenness threshold in random CSPs\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EFreezing is a key part of the clustering phenomenon that is hypothesized by non-rigorous techniques from statistical physics. Indeed, it has been shown that for different kinds of random CSPs (coloring, SAT, xor-sat, and other families), if the constraint-density of a random CSP, F, in our family is greater than r_f then for almost every solution of F, a linear number of variables are frozen, meaning that their colours cannot be changed by a sequence of alterations in which we change o(n) variables at a time, always switching to another solution. If the constraint-density is less than r_f, then almost every solution has o(n) frozen variables.\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;The understanding of clustering has led to the development of advanced heuristics such as Survey Propagation. It has been suggested that the freezing threshold is a precise algorithmic barrier.\u0026nbsp; There is reason to believe that for densities below r_f the random CSPs can be solved using very simple algorithms, while for densities above r_f one requires more sophisticated techniques in order to deal with frozen clusters.\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;In this talk we will explain the current state of the art regarding the appearance of frozenness in random CSPs and we\u0027ll explain some of the tecniques used to analitically study such a phenomena.\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Ricardo Restrepo presents a talk as part of the ARC Colloquium series."}],"uid":"27263","created_gmt":"2013-03-28 10:04:44","changed_gmt":"2017-04-13 21:24:03","author":"Elizabeth Ndongi","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2013-04-01T14:30:00-04:00","event_time_end":"2013-04-01T15:30:00-04:00","event_time_end_last":"2013-04-01T15:30:00-04:00","gmt_time_start":"2013-04-01 18:30:00","gmt_time_end":"2013-04-01 19:30:00","gmt_time_end_last":"2013-04-01 19:30:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"50875","name":"School of Computer Science"},{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78751","name":"Undergraduate students"},{"id":"78761","name":"Faculty\/Staff"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:ndongi@cc.gatech.edu\u0022\u003Endongi@cc.gatech.edu\u003C\/a\u003E\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"254491":{"#nid":"254491","#data":{"type":"event","title":"ARC Colloquium: Adam Marcus, Crisply.com and Yale University","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ESpeaker:\u003C\/strong\u003E Adam Marcus\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E Interlacing Families and Bipartite Ramanujan Graphs\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003EWe will outline the proof that shows the existence of bipartite Ramanujan Graphs of any degree as well as some of mixed degrees. Our approach uses the idea of Bilu and Linial to show that there exists a 2-lift of a given Ramanujan graph which maintains the Ramanujan property.\u0026nbsp; This will include introducing a new technique for establishing the existence of certain combinatorial objects that we call the \u0022Method of Interlacing Polynomials.\u0022\u003C\/p\u003E\u003Cp\u003EThis talk is intended to be accessible by a general computer science audience, and represents joint work with Dan Spielman and Nikhil Srivastava.\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":"","uid":"27263","created_gmt":"2013-11-14 10:30:10","changed_gmt":"2017-04-13 21:23:51","author":"Elizabeth Ndongi","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2013-12-09T14:00:00-05:00","event_time_end":"2013-12-09T14:00:00-05:00","event_time_end_last":"2013-12-09T14:00:00-05:00","gmt_time_start":"2013-12-09 19:00:00","gmt_time_end":"2013-12-09 19:00:00","gmt_time_end_last":"2013-12-09 19:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"47223","name":"College of Computing"},{"id":"50875","name":"School of Computer Science"},{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78751","name":"Undergraduate students"},{"id":"78761","name":"Faculty\/Staff"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:ndongi@cc.gatech.edu\u0022\u003Endongi@cc.gatech.edu\u003C\/a\u003E\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"254811":{"#nid":"254811","#data":{"type":"event","title":"ARC Colloquium: Sivan Sabato, Microsoft Research New England","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ESpeaker:\u003C\/strong\u003E Sivan Sabato\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E \u003Cstrong\u003EAuditing: Active Learning with Outcome-Dependent Query Costs\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003EWe propose a learning setting in which unlabeled data is free, and the cost of a label depends on its value, which is not known in advance. Specifically, we study binary classification in an extreme case, where the algorithm only pays for negative labels. Our motivation is applications such as fraud detection, in which investigating an honest transaction should be avoided if possible. We term the setting \u0022auditing\u0022, and consider the \u0022auditing complexity\u0022 of an algorithm. We design auditing algorithms for simple hypothesis classes, \u003Cbr \/\u003E and show that with these algorithms, the auditing complexity can be significantly lower than the active label complexity. We also consider a general competitive approach for auditing,\u003C\/p\u003E\u003Cp\u003Eand demonstrate its potential for linear classification.\u003C\/p\u003E\u003Cp\u003EJoint work with Anand Sarwate and Nati Srebro from TTI-Chicago\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":"","uid":"27263","created_gmt":"2013-11-14 17:00:32","changed_gmt":"2017-04-13 21:23:51","author":"Elizabeth Ndongi","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2013-11-25T12:00:00-05:00","event_time_end":"2013-11-25T12:00:00-05:00","event_time_end_last":"2013-11-25T12:00:00-05:00","gmt_time_start":"2013-11-25 17:00:00","gmt_time_end":"2013-11-25 17:00:00","gmt_time_end_last":"2013-11-25 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"47223","name":"College of Computing"},{"id":"50875","name":"School of Computer Science"},{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78751","name":"Undergraduate students"},{"id":"78761","name":"Faculty\/Staff"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:ndongi@cc.gatech.edu\u0022\u003Endongi@cc.gatech.edu\u003C\/a\u003E\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"272911":{"#nid":"272911","#data":{"type":"event","title":"ARC Colloquium: Marco Molinaro - School of Industrial \u0026 Systems Engineering at Georgia Tech.","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E Beating the Direct Sum Theorem in Communication Complexity with Implications for Sketching.\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003Cstrong\u003EAbstract:\u003C\/strong\u003E A direct sum theorem for two parties and a function f states that the communication cost of solving k copies of f simultaneously with error probability 1\/3 is at least k R_{1\/3}(f), where R_{1\/3}(f) is the communication required to solve a single copy of f with error probability 1\/3. We improve this for a natural family of functions f, showing that the 1-way communication required to solve k copies of f simultaneously with probability 2\/3 is Omega(k R_{1\/k}(f)). Since R_{1\/k}(f) may be as large as Omega(R_{1\/3}(f) log k), we asymptotically beat the direct sum bound for such functions, showing that the trivial upper bound of solving each of the k copies of f with probability 1-O(1\/k) and taking a union bound is optimal! In order to achieve this, our direct sum involves a novel measure of information cost which allows a protocol to abort with constant probability, and otherwise must be correct with very high probability. Moreover, for the functions considered, we show strong lower bounds on the communication cost of protocols with these relaxed guarantees; indeed, our lower bounds match those for protocols that are not allowed to abort.\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EIn the distributed and streaming models, where one wants to be correct not only on a single query, but simultaneously on a sequence of n queries, we obtain optimal lower bounds on the communication or space complexity. Lower bounds obtained from our direct sum result show that a number of techniques in the sketching literature are optimal, including the following:\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E- (JL transform) Lower bound of Omega((1\/eps^2) log(n\/delta)) on the dimension of (oblivious) Johnson-Lindenstrauss transforms.\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E- (l_p-estimation) Lower bound for the size of encodings of n vectors in [-M, M]^d that allow l_1 or l_2-estimation of Omega((n\/eps^2) log (n\/delta) (log d + log M)).\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E- (Matrix sketching) Lower bound of Omega((1\/eps^2) log n\/delta) on the dimension of a matrix sketch S satisfying the entrywise guarantee |(ASS^TB)_{i,j} - (AB)_{i,j}| \u0026lt;= eps |A_i|_2 |B^j|_2.\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E- (Database joins) Lower bound of Omega((n\/eps^2) log(n\/delta) log M) for sketching frequency vectors of n tables in a database, each with M records, in order to allow join size estimation.\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EJoint work with David P. Woodruff and Grigory Yaroslavtsev.\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Beating the Direct Sum Theorem in Communication Complexity with Implications for Sketching"}],"uid":"27263","created_gmt":"2014-02-03 12:19:43","changed_gmt":"2017-04-13 21:23:16","author":"Elizabeth Ndongi","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2014-02-17T12:30:00-05:00","event_time_end":"2014-02-17T12:30:00-05:00","event_time_end_last":"2014-02-17T12:30:00-05:00","gmt_time_start":"2014-02-17 17:30:00","gmt_time_end":"2014-02-17 17:30:00","gmt_time_end_last":"2014-02-17 17:30:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78751","name":"Undergraduate students"},{"id":"78761","name":"Faculty\/Staff"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:ndongi@cc.gatech.edu\u0022\u003Endongi@cc.gatech.edu\u003C\/a\u003E\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"273011":{"#nid":"273011","#data":{"type":"event","title":"ARC Colloquium: CHEUNG Yun Kuen  - New York University","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E Tatonnement \u0026nbsp;Beyond Gross Substitutes? Gradient Descent to the Rescue\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EWalras, while defining the quintessential notion of market equilibrium in 1874, also gave a\u0026nbsp;simple and natural rule for updating prices and called it the tatonnement process. \u0026nbsp;Does the tatonnement process converge to equilibrium prices? This was a central question in mathematical economics for almost a century. Positive news came in the 1950s,\u0026nbsp;when convergence \u0026nbsp;was\u0026nbsp;established for the gross substitutes case. However, it was followed by negative news in the 1960s: an example by Scarf on which tatonnement cycles and the Sonnenschein-Debreu-Mantel theorem which showed that the task was hopeless for a general Arow-Debreu market.\u003C\/p\u003E\u003Cp\u003E\u0026nbsp; In this work we have, for the first time, gone beyond the gross substitutes case.\u0026nbsp;We define a class of markets for which tatonnement is equivalent to gradient descent. This is the class of markets for which there is a convex potential function whose gradient is always equal to the negative of the excess demand. We call this class the Convex Potential Function (CPF) markets. We show the following results:\u003C\/p\u003E\u003Cp\u003E\u0026nbsp; - CPF markets contain the class of Eisenberg Gale (EG) markets, defined previously by Jain and Vazirani.\u003C\/p\u003E\u003Cp\u003E\u0026nbsp; - The subclass of CPF markets for which the demand is a differentiable function contains exactly those markets whose demand function has a symmetric negative semi-definite Jacobian.\u003C\/p\u003E\u003Cp\u003E\u0026nbsp; - We define a family of continuous versions of tatonnement based on gradient descent using a Bregman divergence. As we show, for many CPF markets, every process in this family will converge to an equilibrium and the process based on KL-divergence will converge for even more of these markets. This is analogous to the classic result for markets satisfying the Weak Gross Substitutes property. We use the theory of differential inclusions, a generalization of differential equations, to establish this result.\u003C\/p\u003E\u003Cp\u003E\u0026nbsp; - A discrete version of tatonnement converges toward the equilibrium for Fisher markets with buyers having CES or Leontief utility functions; the convergence rates for these settings are analyzed using a common potential function. For the CES case, we prove that the tatonnement converges linearly by showing that the potential function satisfies strong sandwiching property, which is reminiscent of strong convexity.\u003C\/p\u003E\u003Cp\u003E\u0026nbsp; I will also discuss our recent results on:\u003C\/p\u003E\u003Cp\u003E\u0026nbsp; - ongoing Fisher markets, a model proposed by Cole and Fleischer. In this model, price updates are asynchronous, and warehouses are incorporated to meet excess demand and store excess supply;\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;- Fisher markets with NCES utility functions, a generalization of CES utility functions.\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;Joint work with Richard Cole and Nikhil Devanur.\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Tatonnement  Beyond Gross Substitutes? Gradient Descent to the Rescue"}],"uid":"27263","created_gmt":"2014-02-03 15:03:04","changed_gmt":"2017-04-13 21:23:16","author":"Elizabeth Ndongi","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2014-02-24T12:30:00-05:00","event_time_end":"2014-02-24T12:30:00-05:00","event_time_end_last":"2014-02-24T12:30:00-05:00","gmt_time_start":"2014-02-24 17:30:00","gmt_time_end":"2014-02-24 17:30:00","gmt_time_end_last":"2014-02-24 17:30:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"47223","name":"College of Computing"},{"id":"50875","name":"School of Computer Science"},{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78751","name":"Undergraduate students"},{"id":"78761","name":"Faculty\/Staff"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:ndongi@cc.gatech.edu\u0022\u003Endongi@cc.gatech.edu\u003C\/a\u003E\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"276131":{"#nid":"276131","#data":{"type":"event","title":"ARC Colloquium: Pratik Worah - New York University","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle\u003C\/strong\u003E: CSPs, Approximation Resistance, and Optimization Hierarchies\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAbstract\u003C\/strong\u003E:\u003C\/p\u003E\u003Cp\u003EA k-ary boolean predicate f, naturally implies a canonical constraint satisfaction problem (CSP(f)). Let MAX k-CSP(f) denote the problem of finding the maximum fraction of simultaneously satisfiable constraints in any given instance of CSP(f). A trivial randomized algorithm achieves an approximation factor proportional to f^{-1}(1).\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;On the other hand, it is known, for some f, that an efficient algorithm can not perform strictly better than the trivial algorithm - such f are known as approximation resistant.\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;One of the main problems in this area is to characterize which predicates are approximation resistant.\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;In this talk, I will survey known bounds for CSPs and their connections with LP and SDP hierarchies. Finally, I will give an overview of my recent research in this area, which gives a characterization of approximation resistance.\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;(Joint with S.Khot and M.Tulsiani).\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"CSPs, Approximation Resistance, and Optimization Hierarchies"}],"uid":"27263","created_gmt":"2014-02-14 16:01:41","changed_gmt":"2017-04-13 21:23:11","author":"Elizabeth Ndongi","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2014-02-26T12:30:00-05:00","event_time_end":"2014-02-26T12:30:00-05:00","event_time_end_last":"2014-02-26T12:30:00-05:00","gmt_time_start":"2014-02-26 17:30:00","gmt_time_end":"2014-02-26 17:30:00","gmt_time_end_last":"2014-02-26 17:30:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"47223","name":"College of Computing"},{"id":"50875","name":"School of Computer Science"},{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78751","name":"Undergraduate students"},{"id":"78761","name":"Faculty\/Staff"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:ndongi@cc.gatech.edu\u0022\u003Endongi@cc.gatech.edu\u003C\/a\u003E\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"277121":{"#nid":"277121","#data":{"type":"event","title":"ARC Colloquium: Michael O. Rabin, Harvard University, Columbia University","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u0026nbsp;Practically Efficient ZKPs for Preventing Collusion in Auctions\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EIn an important mechanism for sealed bid auctions developed by Vickrey and rewarded by a Nobel Prize, the highest bidder gets the item and pays the second highest bid value. Vickrey proved that for these auctions the best strategy for a participant is to bid his private true value for the item. Despite this advantage, second-price auctions are rarely used because they are subject to collusion of bidders. Employing novel cryptography we show that collusion can be avoided thus solving a long standing open problem. The talk will be generally accessible. Joint work with Silvio Micali.\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Practically Efficient ZKPs for Preventing Collusion in Auctions"}],"uid":"27263","created_gmt":"2014-02-18 13:26:15","changed_gmt":"2017-04-13 21:23:08","author":"Elizabeth Ndongi","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2014-03-10T16:30:00-04:00","event_time_end":"2014-03-10T17:30:00-04:00","event_time_end_last":"2014-03-10T17:30:00-04:00","gmt_time_start":"2014-03-10 20:30:00","gmt_time_end":"2014-03-10 21:30:00","gmt_time_end_last":"2014-03-10 21:30:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"47223","name":"College of Computing"},{"id":"50875","name":"School of Computer Science"},{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78751","name":"Undergraduate students"},{"id":"78761","name":"Faculty\/Staff"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:ndongi@cc.gatech.edu\u0022\u003Endongi@cc.gatech.edu\u003C\/a\u003E\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"277141":{"#nid":"277141","#data":{"type":"event","title":"ARC Colloquium: Michael O. Rabin, Harvard University, Columbia University","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E Electronic Voting Using The\u0026nbsp; Split Value Representation\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EWe present an e-voting system wherein votes are represented to the vote-tallying center in the form COM(X) = (COM(u) , COM(v)) , vote = val(X) = (u + v) mod p. The voter gets a paper receipt for COM(X). His actual vote remains secret and he cannot be coerced to cast a specified vote. Vote tallying retains secrecy of individual votes while producing and posting a publicly verifiable proof of correctness of announced election results. The presentation will be generally accessible. Joint work with Ron Rivest.\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Electronic Voting using the Split Value Representation"}],"uid":"27263","created_gmt":"2014-02-18 13:35:38","changed_gmt":"2017-04-13 21:23:08","author":"Elizabeth Ndongi","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2014-03-11T16:00:00-04:00","event_time_end":"2014-03-11T17:00:00-04:00","event_time_end_last":"2014-03-11T17:00:00-04:00","gmt_time_start":"2014-03-11 20:00:00","gmt_time_end":"2014-03-11 21:00:00","gmt_time_end_last":"2014-03-11 21:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"47223","name":"College of Computing"},{"id":"50875","name":"School of Computer Science"},{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78751","name":"Undergraduate students"},{"id":"78761","name":"Faculty\/Staff"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:ndongi@cc.gatech.edu\u0022\u003Endongi@cc.gatech.edu\u003C\/a\u003E\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"278451":{"#nid":"278451","#data":{"type":"event","title":"ARC Colloquium: Grigory Yaroslavtsev, Brown University","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E The Big Data Theory and Randomized Algorithms\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EAdvances in machine learning and developments in modern massive parallel computational systems motivate a large number of challenging questions for the theory of computing. How to make sense of massive amounts of noisy data? How to cluster billions of points and compare large images? How to design scalable algorithms for distributed systems?\u003C\/p\u003E\u003Cp\u003EI will present examples of settings in which these questions can be addressed through the design of randomized algorithms:\u003C\/p\u003E\u003Cul\u003E\u003Cli\u003ESublinear algorithms for testing properties of high-dimensional noisy data such (e.g. monotonicity, the Lipschitz property and convexity)\u003C\/li\u003E\u003Cli\u003EDistributed algorithms for geometric problems in Euclidean space (minimum cost spanning tree, Earth-Mover Distance)\u003C\/li\u003E\u003C\/ul\u003E\u003Cp\u003EThrough these examples I will illustrate how information-theoretic measures of performance such as query complexity and the number of rounds of communication play a key role in the design and analysis of such algorithms. I will show that even in the worst-case these fundamental problems can be solved almost optimally with respect to these measures. The information-theoretic nature is crucial here since lower bounds can be proved unconditionally, i.e. with no computational hardness assumptions.\u003C\/p\u003E\u003Cp\u003EThis talk will be primarily based on two papers which will appear in STOC\u201914 (joint work with Andoni, Berman, Nikolov, Onak and Raskhodnikova) as well as other work by the speaker.\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"The Big Data Theory and Randomized Algorithms"}],"uid":"27263","created_gmt":"2014-02-24 13:46:06","changed_gmt":"2017-04-13 21:23:06","author":"Elizabeth Ndongi","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2014-03-05T18:00:00-05:00","event_time_end":"2014-03-05T18:00:00-05:00","event_time_end_last":"2014-03-05T18:00:00-05:00","gmt_time_start":"2014-03-05 23:00:00","gmt_time_end":"2014-03-05 23:00:00","gmt_time_end_last":"2014-03-05 23:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78751","name":"Undergraduate students"},{"id":"78761","name":"Faculty\/Staff"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:ndongi@cc.gatech.edu\u0022\u003Endongi@cc.gatech.edu\u003C\/a\u003E\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"283031":{"#nid":"283031","#data":{"type":"event","title":"ARC Colloquium: Atri Rudra - University at Buffalo, SUNY","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E A Tale of Two Join Algorithms\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EIn this talk we will talk about two new database join algorithms with provable optimality guarantees.\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;We first present a recent algorithm (PODS 2012) that is the first provably optimal (worst-case) algorithm to compute database joins. As a special case, this join algorithm implies (i) The first algorithmic versions of some well-known geometric inequalities due to Loomis and Whitney (and their generalizations by Bollobas and Thomason); (ii) Algorithmically list recoverable codes that work with parameters that no known algorithmic list recovery result work with (e.g. those based on the Reed-Solomon codes) and an application of this result in designing sublinear time decodable compressed sensing schemes; (ii) Worst-case optimal algorithm to list all occurrences of any fixed hypergraph H in a given large hypergraph G.\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;The second algorithm (PODS 2014) has stronger optimality guarantees: we present an adaptive join algorithm whose run time depends on the \u0022difficulty\u0022 of the data. We believe that this algorithm has more practical applications since worst-case optimal algorithms might have terrible performance on \u0022real data.\u0022 As a special case, we present an (almost) instance optimal algorithm (with respect to comparison based algorithms) for a large class of join queries (namely Fagin\u0027s \\beta-acyclic queries).\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;The talk will be self-contained and is based on join(t) works with Ngo, Nguyen, Porat and Re.\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"A Tale of Two Join Algorithms"}],"uid":"27263","created_gmt":"2014-03-13 11:08:18","changed_gmt":"2017-04-13 21:22:56","author":"Elizabeth Ndongi","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2014-03-24T18:30:00-04:00","event_time_end":"2014-03-24T18:30:00-04:00","event_time_end_last":"2014-03-24T18:30:00-04:00","gmt_time_start":"2014-03-24 22:30:00","gmt_time_end":"2014-03-24 22:30:00","gmt_time_end_last":"2014-03-24 22:30:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78751","name":"Undergraduate students"},{"id":"78761","name":"Faculty\/Staff"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:ndongi@cc.gatech.edu\u0022\u003Endongi@cc.gatech.edu\u003C\/a\u003E\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"284621":{"#nid":"284621","#data":{"type":"event","title":"ARC Seminar\/DOS: Samuel Fiorini - Universit\u00e9 libre de Brussels (Brussels, Belgium).","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E Cut-dominant and forbidden minors\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EThe cut-dominant of a connected graph G is the polyhedron that corresponds to the problem of computing global min-cuts in G. Despite the fact that computing a global min-cut can be done in polynomial time, the geometry of the cut-dominant is far from being understood. We study graphs for which all facets of the corresponding cut-dominant have right-hand side at most a fixed integer k. These graphs form a minor-closed collection. We give a complete list of forbidden minors for k \u0026lt;= 2. This is then applied to the TSP to give a shorter proof of a classic result of Fonlupt and Naddef (Math. Prog., 1992) \u0026nbsp;that characterizes TSP-perfect graphs. This work in progress is joint with Kanstantsin Pashkovich (Brussels) and Michele Conforti (Padova).\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Samuel Fiorini will give a talk at the ARC Seminar"}],"uid":"27263","created_gmt":"2014-03-21 08:33:01","changed_gmt":"2017-04-13 21:22:54","author":"Elizabeth Ndongi","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2014-03-26T17:00:00-04:00","event_time_end":"2014-03-26T18:00:00-04:00","event_time_end_last":"2014-03-26T18:00:00-04:00","gmt_time_start":"2014-03-26 21:00:00","gmt_time_end":"2014-03-26 22:00:00","gmt_time_end_last":"2014-03-26 22:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[{"id":"111051","name":"Algorithm and Randomness Center"},{"id":"4265","name":"ARC"},{"id":"6121","name":"DOS"},{"id":"109","name":"Georgia Tech"},{"id":"1808","name":"graduate students"},{"id":"14673","name":"theory"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78751","name":"Undergraduate students"},{"id":"78761","name":"Faculty\/Staff"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:sebastian.pokutta@isye.gatech.edu\u0022\u003Esebastian.pokutta@isye.gatech.edu\u003C\/a\u003E\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"284811":{"#nid":"284811","#data":{"type":"event","title":"ARC Colloquium: Gopal Pandurangan - Brown University (RI) and NTU, Singapore","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp;\u003C\/strong\u003EDistributed Algorithmic Foundations of Dynamic Networks\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EMany of today\u0027s real-world communication networks are highly dynamic, i.e., their network topology changes continuously over time. Examples include Peer-to-Peer (P2P) networks and ad hoc wireless and sensor networks. Such networks are now widely used in various applications, including sharing data and resources, search and storage, Internet telephony, environment monitoring and management. In P2P networks (e.g., Skype, BitTorrent), the topology changes at a rapid rate due to continuous joining and leaving of nodes; in ad hoc sensor and vehicular networks, the topology changes dynamically due to failure or mobility of the nodes. Performing robust and efficient non-trivial distributed computation in such highly dynamic networks is challenging. In this\u0026nbsp;talk, I will give an overview of our recent results that make progress towards developing an algorithmic theory of dynamic networks. First, I will present a rigorous theoretical framework for studying dynamic networks. Then I will present efficient techniques and algorithms for solving the fundamental agreement problem in dynamic networks. I will also present efficient algorithms for key problems such as information spreading, search, and storage. To complement our algorithms, I will also present almost tight lower bounds for agreement and information spreading.\u0026nbsp;\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Distributed Algorithmic Foundations of Dynamic Networks"}],"uid":"27263","created_gmt":"2014-03-24 07:48:41","changed_gmt":"2017-04-13 21:22:52","author":"Elizabeth Ndongi","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2014-04-28T18:30:00-04:00","event_time_end":"2014-04-28T18:30:00-04:00","event_time_end_last":"2014-04-28T18:30:00-04:00","gmt_time_start":"2014-04-28 22:30:00","gmt_time_end":"2014-04-28 22:30:00","gmt_time_end_last":"2014-04-28 22:30:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"47223","name":"College of Computing"},{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78751","name":"Undergraduate students"},{"id":"78761","name":"Faculty\/Staff"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:ndongi@cc.gatech.edu\u0022\u003Endongi@cc.gatech.edu\u003C\/a\u003E\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"290061":{"#nid":"290061","#data":{"type":"event","title":"ARC Colloquium: Howard Karloff - Yahoo Labs","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle\u003C\/strong\u003E: Maximum Entropy Summary Trees\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EGiven a very large, node-weighted, rooted tree on, say, n nodes, if one has only enough space to display a k-node summary of the tree, what is the most informative way to draw the tree?\u0026nbsp; We define a type of weighted tree that we call a \u0022summary tree\u0022 of the original tree, that results from aggregating nodes of the original tree subject to certain constraints. We suggest that the best choice of which summary tree to use (among those with a fixed number of nodes) is the one that maximizes the information-theoretic entropy of a natural probability distribution associated with the summary tree, and we provide a (pseudopolynomial-time) dynamic-programming algorithm to compute this maximum entropy summary tree, when the weights are integral. The result is an automated way to summarize large trees and retain as much information about them as possible, while using (and displaying) only a fraction of the original node set.\u0026nbsp; We also provide an additive approximation algorithm and a greedy heuristic that are faster than the optimal algorithm, and generalize to trees with real-valued weights.\u003C\/p\u003E\u003Cp\u003EThis is joint work with Ken Shirley of ATT Labs and Richard Cole of NYU.\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Maximum Entropy Summary Trees"}],"uid":"27263","created_gmt":"2014-04-11 10:27:21","changed_gmt":"2017-04-13 21:22:44","author":"Elizabeth Ndongi","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2014-04-24T16:00:00-04:00","event_time_end":"2014-04-24T16:00:00-04:00","event_time_end_last":"2014-04-24T16:00:00-04:00","gmt_time_start":"2014-04-24 20:00:00","gmt_time_end":"2014-04-24 20:00:00","gmt_time_end_last":"2014-04-24 20:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78751","name":"Undergraduate students"},{"id":"78761","name":"Faculty\/Staff"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:ndongi@cc.gatech.edu\u0022\u003Endongi@cc.gatech.edu\u003C\/a\u003E\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"336011":{"#nid":"336011","#data":{"type":"event","title":"ARC Colloquium: Bartosz Walczak - School of Mathematics, Georgia Tech","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle: \u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EOn-line Approach to Off-line Graph Coloring Problems\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EThe on-line graph coloring problem is modeled by a game between two players: Presenter, who constructs a graph of some fixed class presenting new vertices one by one, and Algorithm, who colors each vertex right after it is presented without the possibility of changing the color afterwards. The goal of Algorithm is to use as few colors as possible, while Presenter tries to force Algorithm to use many colors. Any game of this kind gives rise to a new class of graphs, called game graphs, which \u0022encode\u0022 strategies of Presenter in the game. The chromatic number of such a game graph is equal to the number of colors that Algorithm is forced to use playing against the corresponding strategy. It turns out that game graphs of appropriately defined games can be modeled as intersection graphs of geometric objects. This is the key idea which combined with on-line competitivity analysis and graph decomposition techniques yields lower and upper bounds on the maximum possible chromatic number in various classes of geometric intersection graphs. I will survey results obtained with this method, present in detail its application to constructing triangle-free geometric intersection graphs with arbitrarily large chromatic number (solution to a problem of Erd\u0151s from the 1970s), and discuss several open problems that arose from this research. This is my joint work with various coauthors during last 2 years.\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EARC:\u003C\/strong\u003E \u003Ca href=\u0022http:\/\/www.arc.gatech.edu\/\u0022\u003Ehttp:\/\/www.arc.gatech.edu\/\u003C\/a\u003E\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"On-line Approach to Off-line Graph Coloring Problems"}],"uid":"27466","created_gmt":"2014-10-21 17:29:45","changed_gmt":"2017-04-13 21:21:22","author":"Dani Denton","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2014-10-27T14:00:00-04:00","event_time_end":"2014-10-27T15:00:00-04:00","event_time_end_last":"2014-10-27T15:00:00-04:00","gmt_time_start":"2014-10-27 18:00:00","gmt_time_end":"2014-10-27 19:00:00","gmt_time_end_last":"2014-10-27 19:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"50875","name":"School of Computer Science"},{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78751","name":"Undergraduate students"},{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003Edenton at cc dot gatech dot edu\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"340101":{"#nid":"340101","#data":{"type":"event","title":"ARC Colloquium: Siu On Chan - Microsoft Research","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle: \u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EEfficient Density Estimation via Piecewise Polynomial Approximation\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EWe give a highly efficient \u0022semi-agnostic\u0022 algorithm for learning univariate probability distributions that are well approximated by piecewise polynomial density functions. Let p be an arbitrary distribution over an interval I which is \u03c4-close (in total variation distance) to an unknown probability distribution q that is defined by an unknown partition of I into t intervals and t unknown degree-d polynomials specifying q over each of the intervals. We give an algorithm that draws O~(t (d+1)\/\u03b5^2) samples from p, runs in time poly(t,d,1\/ \u03b5), and with high probability outputs a piecewise polynomial hypothesis distribution h that is (O(\u03c4)+\u03b5)-close (in total variation distance) to p. This sample complexity is essentially optimal; we show that even for \u03c4=0, any algorithm that learns an unknown t-piecewise degree-d probability distribution over I to accuracy \u03b5 must use \u03a9(t(d+1)\/(polylog(d+1) \u03b5^2)) samples from the distribution, regardless of its running time. Our algorithm combines tools from approximation theory, uniform convergence, linear programming, and dynamic programming.\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EWe apply this general algorithm to obtain a wide range of results for many natural problems in density estimation over both continuous and discrete domains. These include state-of-the-art results for learning mixtures of log-concave distributions; mixtures of t-modal distributions; mixtures of Monotone Hazard Rate distributions; mixtures of Poisson Binomial Distributions; mixtures of Gaussians; and mixtures of k-monotone densities. Our general technique yields computationally efficient algorithms for all these problems, in many cases with provably optimal sample complexities (up to logarithmic factors) in all parameters.\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EShort Bio:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003ESiu On Chan is a Postdoc at Microsoft Research. He did his undergrad in Chinese University of Hong Kong, MSc at University of Toronto, and PhD at UC Berkeley. He is interested in studying the limitations of approximation algorithms, in terms of NP-hardness and integrality gaps of convex programming hierarchies. He is also interested in random graphs and property testing. He received a Best Paper Award at STOC 2013.\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Efficient Density Estimation via Piecewise Polynomial Approximation"}],"uid":"27466","created_gmt":"2014-11-03 17:42:36","changed_gmt":"2017-04-13 21:21:17","author":"Dani Denton","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2014-11-10T12:00:00-05:00","event_time_end":"2014-11-10T12:00:00-05:00","event_time_end_last":"2014-11-10T12:00:00-05:00","gmt_time_start":"2014-11-10 17:00:00","gmt_time_end":"2014-11-10 17:00:00","gmt_time_end_last":"2014-11-10 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"47223","name":"College of Computing"},{"id":"50875","name":"School of Computer Science"},{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78751","name":"Undergraduate students"},{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003Edenton at cc dot gatech dot edu\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"347901":{"#nid":"347901","#data":{"type":"event","title":"ARC Colloquium and ACO Student Seminar: Umesh Vazirani - U. C. Berkeley","body":[{"value":"\u003Cp\u003ETitle:\u003Cbr \/\u003EHow \u201cQuantum\u201d is the D-Wave Machine?\u003Cbr \/\u003E\u003Cbr \/\u003EAbstract:\u003Cbr \/\u003EA special purpose \u0022quantum computer\u0022 manufactured by the Canadian company D-Wave has led to intense excitement in the mainstream media (including a Time magazine cover dubbing it \u0022the infinity machine\u0022) and the computer industry, and a lively debate in the academic community. Scientifically it leads to the interesting question of whether it is possible to obtain quantum effects on a large scale with qubits that are not individually well protected from decoherence. \u003Cbr \/\u003E\u003Cbr \/\u003EWe propose a simple and natural classical model for the D-Wave machine - replacing their superconducting qubits with classical magnets, coupled with nearest neighbor interactions whose strength is taken from D-Wave\u0027s specifications. The behavior of this classical model agrees remarkably well with posted experimental data about the input-output behavior of the D-Wave machine. \u003Cbr \/\u003E\u003Cbr \/\u003EFurther investigation of our classical model shows that despite its simplicity, it exhibits novel algorithmic properties. Its behavior is fundamentally different from that of its close cousin, classical heuristic simulated annealing. In particular, the major motivation behind the D-Wave machine was the hope that it would tunnel through local minima in the energy landscape, minima that simulated annealing got stuck in. The reproduction of D-Wave\u0027s behavior by our classical model demonstrates that tunneling on a large scale may be a more subtle phenomenon than was previously understood. \u003Cbr \/\u003E\u003Cbr \/\u003EIn this talk I will try to make these results accessible to a general computer science audience, as well as discuss future prospects for quantum annealing based quantum computers. \u003Cbr \/\u003E\u003Cbr \/\u003EBased on joint work with Seung Woo Shin, Graheme Smith, and John Smolin.\u003Cbr \/\u003E\u003Cbr \/\u003E\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"How \u201cQuantum\u201d is the D-Wave Machine?"}],"uid":"27466","created_gmt":"2014-11-20 17:27:22","changed_gmt":"2017-04-13 21:21:03","author":"Dani Denton","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2014-11-21T12:00:00-05:00","event_time_end":"2014-11-21T13:00:00-05:00","event_time_end_last":"2014-11-21T13:00:00-05:00","gmt_time_start":"2014-11-21 17:00:00","gmt_time_end":"2014-11-21 18:00:00","gmt_time_end_last":"2014-11-21 18:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"47223","name":"College of Computing"},{"id":"50875","name":"School of Computer Science"},{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78751","name":"Undergraduate students"},{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003Edenton at cc dot gatech edu\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"349151":{"#nid":"349151","#data":{"type":"event","title":"ARC Colloquium: Brittany Terese Fasy\u2013Tulane University","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003E(Note: location changed to CCB 102)\u003Cbr \/\u003E\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp;\u003C\/strong\u003E Providing Statistical Guarantees for Topological Summaries of Data\u003C\/p\u003E\u003Cp\u003E\u003Cbr \/\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003Cbr \/\u003EPersistent homology is a method for probing topological properties of point clouds and function. The method involves tracking the birth and death of topological features as one varies a tuning parameter. Features with short lifetimes are informally considered to be \u201ctopological noise.\u201d I am interested in bringing statistical ideas to persistent homology in order to distinguish topological signal from topological noise and to derive meaningful, yet computable, summaries of large datasets.\u0026nbsp; In this talk, I will define some of the existing topological summaries of data, and show how we can provide statistical guarantees of these summaries.\u003Cbr \/\u003E\u003Ca href=\u0022http:\/\/www.fasy.us\u0022 target=\u0022_blank\u0022\u003Ewww.fasy.us\u003C\/a\u003E\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Providing Statistical Guarantees for Topological Summaries of Data"}],"uid":"27466","created_gmt":"2014-11-25 19:04:53","changed_gmt":"2017-04-13 21:21:01","author":"Dani Denton","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2014-12-08T12:00:00-05:00","event_time_end":"2014-12-08T12:00:00-05:00","event_time_end_last":"2014-12-08T12:00:00-05:00","gmt_time_start":"2014-12-08 17:00:00","gmt_time_end":"2014-12-08 17:00:00","gmt_time_end_last":"2014-12-08 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"hg_media":{"350171":{"id":"350171","type":"image","title":"Brittany Terese Fasy","body":null,"created":"1449245702","gmt_created":"2015-12-04 16:15:02","changed":"1475895075","gmt_changed":"2016-10-08 02:51:15","alt":"Brittany Terese Fasy","file":{"fid":"201081","name":"brittany-fasy.jpg","image_path":"\/sites\/default\/files\/images\/brittany-fasy_0.jpg","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/images\/brittany-fasy_0.jpg","mime":"image\/jpeg","size":117529,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/images\/brittany-fasy_0.jpg?itok=Sd-ddLQ_"}}},"media_ids":["350171"],"groups":[{"id":"47223","name":"College of Computing"},{"id":"50875","name":"School of Computer Science"},{"id":"70263","name":"ARC"}],"categories":[],"keywords":[{"id":"5660","name":"algorithms"},{"id":"438","name":"data"},{"id":"111251","name":"Guarantees"},{"id":"4584","name":"randomness"},{"id":"168002","name":"Statistical"},{"id":"111261","name":"Topological"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1789","name":"Conference\/Symposium"}],"invited_audience":[{"id":"78751","name":"Undergraduate students"},{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EDani Denton\u003Cbr \/\u003E\u003Ca href=\u0022mailto:denton@cc.gatech.edu\u0022\u003Edenton@cc.gatech.edu\u003C\/a\u003E\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"349751":{"#nid":"349751","#data":{"type":"event","title":"ARC Colloquium: Seth Pettie\u2013University of Michigan","body":[{"value":"\u003Cp\u003E(Refreshments will be served in Klaus 2222 at 2 pm)\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E \u003Cbr \/\u003EWeighted Matching on General Graphs: Faster and Simpler\u003Cbr \/\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAbstract :\u003C\/strong\u003E\u003Cbr \/\u003EWe present a new scaling algorithm for maximum (or minimum) weight perfect matching on general, edge weighted graphs.\u0026nbsp; The algorithm runs in O(mn^{1\/2}log(nW)) time, where m, n, and W are the numbers of edges, vertices and maximum integer edge weight.\u0026nbsp; This bound matches the fastest algorithm for bipartite graphs and comes within a log(nW) factor of the Micali-Vazirani cardinality matching algorithm.\u0026nbsp;\u0026nbsp; In terms of running time our algorithm is just slightly faster than the previous best (Gabow and Tarjan, 1991) by a roughly (log n)^{1\/2} factor.\u0026nbsp; However, it is dramatically simpler to describe and analyze. \u003C\/p\u003E\u003Cp\u003EJoint work with Ran Duan (IIIS, Tsinghua) and Hsin-Hao Su (University of Michigan).\u0026nbsp; Manuscript available at \u003Ca href=\u0022http:\/\/arxiv.org\/abs\/1411.1919v2\u0022 title=\u0022http:\/\/arxiv.org\/abs\/1411.1919v2\u0022\u003Ehttp:\/\/arxiv.org\/abs\/1411.1919v2\u003C\/a\u003E.\u003Cbr \/\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E\u003Cbr \/\u003ESeth Pettie received his Ph.D. in Computer Science from the University of Texas at Austin, in 2003.\u0026nbsp; From 2003-2006 he was an Alexander von Humboldt Postdoctoral Fellow at the Max Planck Institute for Computer Science, in Saarbruecken, Germany.\u0026nbsp; Since 2006 he has been a professor of Electrical Engineering and Computer Science at the University of Michigan, in Ann Arbor.\u003Cbr \/\u003E\u003C\/p\u003E\u003Cp\u003ESeth Pettie, Assoc. Prof. in Computer Science and Engineering University of Michigan, Ann Arbor \u003Ca href=\u0022http:\/\/web.eecs.umich.edu\/~pettie\u0022\u003Ehttp:\/\/web.eecs.umich.edu\/~pettie\u003C\/a\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cbr \/\u003E\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Seth Pettie presents a talk as part of the ARC Colloquium series."}],"uid":"27255","created_gmt":"2014-11-26 14:43:54","changed_gmt":"2017-04-13 21:21:01","author":"Josie Giles","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2015-03-23T14:00:00-04:00","event_time_end":"2015-03-23T15:00:00-04:00","event_time_end_last":"2015-03-23T15:00:00-04:00","gmt_time_start":"2015-03-23 18:00:00","gmt_time_end":"2015-03-23 19:00:00","gmt_time_end_last":"2015-03-23 19:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"hg_media":{"349761":{"id":"349761","type":"image","title":"Seth Pettie","body":null,"created":"1449245696","gmt_created":"2015-12-04 16:14:56","changed":"1475895075","gmt_changed":"2016-10-08 02:51:15","alt":"Seth Pettie","file":{"fid":"201053","name":"seth-pettie.jpg","image_path":"\/sites\/default\/files\/images\/seth-pettie_0.jpg","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/images\/seth-pettie_0.jpg","mime":"image\/jpeg","size":575201,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/images\/seth-pettie_0.jpg?itok=Lf-szEuP"}}},"media_ids":["349761"],"related_links":[{"url":"http:\/\/www.arc.gatech.edu\/","title":"Algorithms \u0026 Randomness Center (ARC)"}],"groups":[{"id":"47223","name":"College of Computing"},{"id":"50875","name":"School of Computer Science"},{"id":"70263","name":"ARC"}],"categories":[],"keywords":[{"id":"111051","name":"Algorithm and Randomness Center"},{"id":"4265","name":"ARC"},{"id":"9267","name":"ARC Colloquium"},{"id":"168003","name":"Seth Pettie"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78751","name":"Undergraduate students"},{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EDani Denton\u003Cbr \/\u003Edenton at cc dot gatech dot edu\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"349781":{"#nid":"349781","#data":{"type":"event","title":"ARC Colloquium: Jamie Morgenstern \u2013 Carnegie Mellon University","body":[{"value":"\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003E(Refreshments served in Klaus 2222 at 2 pm)\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp;\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EApproximately Stable, School Optimal, and Student-Truthful Many-to-One Matchings (via Differential Privacy)\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EWe present a mechanism for computing asymptotically stable school optimal matchings, while guaranteeing that it is an asymptotic dominant strategy for every student to report their true preferences to the mechanism. Our main tool in this endeavor is differential privacy: we give an algorithm that coordinates a stable matching using differentially private signals, which lead to our truthfulness guarantee. This is the first setting in which it is known how to achieve nontrivial truthfulness guarantees for students when computing school-optimal matchings, assuming worst-case preferences (for schools and students) in large markets.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EJoint work with Sampath Kannan, Aaron Roth and Zhiwei Steven Wu: SODA 2015.\u003C\/p\u003E\u003Cp\u003E\u003Cbr \/\u003E\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EJamie Morgenstern presents a talk as part of the ARC Colloquium series on Approximately Stable, School Optimal, and Student-Truthful Many-to-One Matchings (via Differential Privacy)\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Jamie Morgenstern presents a talk as part of the ARC Colloquium series on Approximately Stable, School Optimal, and Student-Truthful Many-to-One Matchings (via Differential Privacy)"}],"uid":"27255","created_gmt":"2014-11-26 15:42:21","changed_gmt":"2017-04-13 21:21:01","author":"Josie Giles","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2015-02-02T12:00:00-05:00","event_time_end":"2015-02-02T13:00:00-05:00","event_time_end_last":"2015-02-02T13:00:00-05:00","gmt_time_start":"2015-02-02 17:00:00","gmt_time_end":"2015-02-02 18:00:00","gmt_time_end_last":"2015-02-02 18:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"hg_media":{"350121":{"id":"350121","type":"image","title":"Jamie Morgenstern","body":null,"created":"1449245702","gmt_created":"2015-12-04 16:15:02","changed":"1475895075","gmt_changed":"2016-10-08 02:51:15","alt":"Jamie Morgenstern","file":{"fid":"201079","name":"jamie-morgenstern.jpg","image_path":"\/sites\/default\/files\/images\/jamie-morgenstern_0.jpg","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/images\/jamie-morgenstern_0.jpg","mime":"image\/jpeg","size":118123,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/images\/jamie-morgenstern_0.jpg?itok=lIxhDUFm"}}},"media_ids":["350121"],"related_links":[{"url":"http:\/\/www.arc.gatech.edu\/","title":"Algorithms \u0026 Randomness Center (ARC)"}],"groups":[{"id":"47223","name":"College of Computing"},{"id":"50875","name":"School of Computer Science"},{"id":"70263","name":"ARC"}],"categories":[],"keywords":[{"id":"111051","name":"Algorithm and Randomness Center"},{"id":"4265","name":"ARC"},{"id":"9267","name":"ARC Colloquium"},{"id":"111071","name":"Jamie Morgenstern"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78751","name":"Undergraduate students"},{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003Edenton at cc dot gatech dot edu\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"350151":{"#nid":"350151","#data":{"type":"event","title":"The Power of Randomness in Computation Workshop","body":[{"value":"\u003Cp\u003EARC presents\u0026nbsp;\u201c\u003Ca href=\u0022http:\/\/www.ima.umn.edu\/2014-2015\/W3.16-20.15\/?event_id=W3.16-20.15\u0022 target=\u0022_blank\u0022\u003EThe Power of Randomness in Computation Workshop\u003C\/a\u003E\u201d, co-sponsored by the\u0026nbsp;Institute for Mathematics and its Applications (IMA)\u0026nbsp;at the University of Minnesota.\u003C\/p\u003E\u003Cp\u003EThis workshop will be held at the Georgia Institute of Technology, Klaus Building room 1116, 266 Ferst Drive, NW, Atlanta, GA 30332-0765.\u003C\/p\u003E\u003Cp\u003EThis workshop will bring together researchers from a variety of fields to highlight new results broadly related to the use of randomization in algorithm design.\u003C\/p\u003E\u003Cp\u003ETalks will highlight new results in the area of randomized algorithms and probabilistic tools for algorithm design. The workshop will also include recent successes in derandomization and problems where there are efficient deterministic algorithms but not yet randomized versions, such as Weitz\u0027s approximate counting approach and recent extensions of it.\u003C\/p\u003E\u003Cp\u003EThe workshop will attempt to bring various experts interested in this general theme and identify challenging open problems and discuss ways to approach and attack them.\u003C\/p\u003E\u003Cp\u003E\u003Cbr \/\u003E\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EARC presents \u201c\u003Ca href=\u0022http:\/\/www.ima.umn.edu\/2014-2015\/W3.16-20.15\/?event_id=W3.16-20.15\u0022 target=\u0022_blank\u0022\u003EThe Power of Randomness in Computation Workshop\u003C\/a\u003E\u201d, co-sponsored by the Institute for Mathematics and its Applications (IMA\u003Ca href=\u0022http:\/\/www.ima.umn.edu\/\u0022 target=\u0022_blank\u0022\u003E)\u003C\/a\u003E at the University of Minnesota.\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"ARC presents \u201cThe Power of Randomness in Computation Workshop,\u201d co-sponsored by the Institute for Mathematics and its Applications (IMA) at the University of Minnesota."}],"uid":"27255","created_gmt":"2014-11-26 16:55:16","changed_gmt":"2017-04-13 21:21:00","author":"Josie Giles","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2015-03-16T10:00:00-04:00","event_time_end":"2015-03-20T18:00:00-04:00","event_time_end_last":"2015-03-20T18:00:00-04:00","gmt_time_start":"2015-03-16 14:00:00","gmt_time_end":"2015-03-20 22:00:00","gmt_time_end_last":"2015-03-20 22:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"related_links":[{"url":"http:\/\/www.ima.umn.edu\/2014-2015\/W3.16-20.15\/?event_id=W3.16-20.15","title":"The Power of Randomness in Computation"},{"url":"http:\/\/www.arc.gatech.edu\/","title":"Algorithms \u0026 Randomness Center (ARC)"},{"url":"http:\/\/www.ima.umn.edu\/","title":"Institute for Mathematics and its Applications"}],"groups":[{"id":"47223","name":"College of Computing"},{"id":"50875","name":"School of Computer Science"},{"id":"70263","name":"ARC"}],"categories":[],"keywords":[{"id":"111051","name":"Algorithm and Randomness Center"},{"id":"4265","name":"ARC"},{"id":"111081","name":"Institute for Mathematics and its Applications"},{"id":"111091","name":"The Power of Randomness in Computation Workshop"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"26411","name":"Training\/Workshop"}],"invited_audience":[{"id":"78751","name":"Undergraduate students"},{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EDani Denton\u003Cbr \/\u003E\u003Ca href=\u0022mailto:denton@cc.gatech.edu\u0022\u003Edenton@cc.gatech.edu\u003C\/a\u003E\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"357761":{"#nid":"357761","#data":{"type":"event","title":"ARC Colloquium: Vitaly Feldman - IBM\/Simons Institute","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp;\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EPreserving Statistical Validity in Adaptive Data Analysis\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EA great deal of effort has been devoted to reducing the risk of spurious scientific discoveries resulting from misapplication of statistical data analysis. Existing approaches to ensuring validity of inferences drawn from data assume a fixed collection of hypotheses to be tested, or analysis to be applied, selected non-adaptively before the data are examined. In contrast, the practice of data analysis in scientific research is by its nature an adaptive process, in which new hypotheses are generated and new analyses are performed on the basis of data exploration and observed outcomes on the same data. We demonstrate a new approach for addressing the challenges of adaptivity based on insights from private data analysis. As an application we show how to safely reuse a holdout set a great many times without undermining its validation power, even when hypotheses, models, and algorithms are chosen adaptively.\u003C\/p\u003E\u003Cp\u003EJoint work with Cynthia Dwork, Moritz Hardt, Toni Pitassi, Omer Reingold and Aaron Roth.\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EVitaly Feldman presents a talk as part of the ARC Colloquium series.\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"ARC Colloquium: Vitaly Feldman"}],"uid":"27466","created_gmt":"2014-12-17 12:03:31","changed_gmt":"2017-04-13 21:20:53","author":"Dani Denton","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2015-01-26T12:00:00-05:00","event_time_end":"2015-01-26T13:00:00-05:00","event_time_end_last":"2015-01-26T13:00:00-05:00","gmt_time_start":"2015-01-26 17:00:00","gmt_time_end":"2015-01-26 18:00:00","gmt_time_end_last":"2015-01-26 18:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"related_links":[{"url":"http:\/\/www.arc.gatech.edu\/","title":"Algorithms \u0026 Randomness Center (ARC)"}],"groups":[{"id":"47223","name":"College of Computing"},{"id":"50875","name":"School of Computer Science"},{"id":"70263","name":"ARC"}],"categories":[],"keywords":[{"id":"112751","name":"(ARC)"},{"id":"114981","name":"Adaptive Data Analysis"},{"id":"111051","name":"Algorithm and Randomness Center"},{"id":"115001","name":"Computational Complexity"},{"id":"114991","name":"Computational Learning Theory"},{"id":"109","name":"Georgia Tech"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78751","name":"Undergraduate students"},{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003Edenton at cc dot gatech dot edu\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"359681":{"#nid":"359681","#data":{"type":"event","title":"ARC Colloquium: Blair Sullivan - North Carolina State University","body":[{"value":"\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003ERefreshments served in Klaus 2222 at 2 pm\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp;\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003ELooking for Structure in Real-World Networks\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EGraphs offer a natural representation of relationships within data -- for example, edges can be defined based on any user-defined measure of similarity (e.g. word frequencies, geographic proximity of observation, gene expression levels, or overlap in sample populations) or interaction (e.g. social friendship, communication, chemical bonds\/protein bindings, or migration). As such, network analysis is playing an increasingly important role in understanding the data collected in a wide variety of social, scientific, and engineering settings.\u0026nbsp; Unfortunately, efficient graph algorithms with guaranteed performance and solution quality are impossible in general networks (according to computational complexity).\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;One tantalizing approach to increasing scalability without sacrificing accuracy is to employ a suite of powerful (parameterized) algorithms developed by the theoretical computer science community which exploit specific forms of sparse graph structure to drastically reduce running time.\u0026nbsp; The applicability of these algorithms, however, is unclear, since the (extensive) research effort in network science to characterize the structure of real-world graphs has been primarily focused on either coarse, global properties (e.g., diameter) or very localized measurements (e.g., clustering coefficient) -- metrics which are insufficient for ensuring efficient algorithms.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;We discuss recent work on bridging the gap between network analysis and structural graph algorithms, answering questions like: Do real-world networks exhibit structural properties that enable efficient algorithms?\u0026nbsp; Is it observable empirically? Can sparse structure be proven for popular random graph models? How does such a framework help? Are the efficient algorithms associated with this structure relevant for common tasks such as evaluating communities, clustering and motifs? Can we reduce the (often super-exponential) dependence of these approaches on their structural parameters?\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EJoint work with E. Demaine, M. Farrell, T. Goodrich, N. Lemons, F. Reidl, P. Rossmanith, F. Sanchez Villaamil \u0026amp; S. Sikdar.\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EBlair Sullivan presents a talk as part of the ARC Colloquiuim series.\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"ARC Colloquium: Blair Sullivan"}],"uid":"27466","created_gmt":"2014-12-31 16:01:09","changed_gmt":"2017-04-13 21:20:51","author":"Dani Denton","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2015-02-16T12:00:00-05:00","event_time_end":"2015-02-16T13:00:00-05:00","event_time_end_last":"2015-02-16T13:00:00-05:00","gmt_time_start":"2015-02-16 17:00:00","gmt_time_end":"2015-02-16 18:00:00","gmt_time_end_last":"2015-02-16 18:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"47223","name":"College of Computing"},{"id":"50875","name":"School of Computer Science"},{"id":"70263","name":"ARC"}],"categories":[],"keywords":[{"id":"12781","name":"algorithms \u0026 randomness center"},{"id":"9267","name":"ARC Colloquium"},{"id":"118411","name":"Blair Sullivan"},{"id":"118401","name":"Looking for Structure in Real-World Networks"},{"id":"14673","name":"theory"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78751","name":"Undergraduate students"},{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003Edenton at cc dot gatech dot edu\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"359741":{"#nid":"359741","#data":{"type":"event","title":"ARC Colloquium\/ACO Student Seminar: Peter Winkler \u2013 Dartmouth College","body":[{"value":"\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003E(Pizza will be served at 1pm in Skiles 005)\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ETitle: \u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EPursuit on a Graph\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003E\u0026nbsp;Abstract:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EPursuit games---motivated historically by military tactics \u2013 are a natural for graphical settings, and take many forms.\u0026nbsp; We will present some recent results involving (among other things) drunks, Kakeya sets and a ``ketchup graph.\u0027\u0027\u0026nbsp; Lastly, we describe what we think is the most important open problem in the field.\u003Cbr \/\u003E \u003Cstrong\u003EBio:\u003C\/strong\u003E\u003Cbr \/\u003E Peter Winkler is William Morrill Professor of Mathematics and Computer Science at Dartmouth College.\u0026nbsp; He is the author of about 150 research papers and holds a dozen patents in marine navigation, cryptolography, holography, gaming, optical networking, and distributed computing.\u0026nbsp; His research is primarily in combinatorics, probability, and the theory of computing, with forays into statistical physics.\u0026nbsp; He is a winner of the Mathematical Association of America\u0027s Lester R. Ford and David P. Robbins prizes.\u003C\/p\u003E\u003Cp\u003EDr. Winkler has also written two collections of mathematical puzzles, a book on cryptography in the game of bridge, and a portfolio of compositions for ragtime piano.\u0026nbsp; He\u0027s working on a new puzzle book.\u003C\/p\u003E\u003Cp\u003EARC: \u003Ca href=\u0022http:\/\/www.arc.gatech.edu\/\u0022\u003Ehttp:\/\/www.arc.gatech.edu\/\u003C\/a\u003E\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EPeter Winkler will be giving a joint ACR Colloquium and ACO Student Seminar on January 16, 2015 at 1:00 pm in Skiles Room 005. - See more at: \u003Ca href=\u0022http:\/\/www.cc.gatech.edu\/events\/arc-colloquium-and-joint-aco-student-seminar-peter-winkler#sthash.bjAYe3Eq.dpuf\u0022 title=\u0022http:\/\/www.cc.gatech.edu\/events\/arc-colloquium-and-joint-aco-student-seminar-peter-winkler#sthash.bjAYe3Eq.dpuf\u0022\u003Ehttp:\/\/www.cc.gatech.edu\/events\/arc-colloquium-and-joint-aco-student-sem...\u003C\/a\u003E\u003C\/p\u003EPeter Winkler will be giving a joint ACR Colloquium and ACO Student Seminar on January 16, 2015 at 1:00 pm in Skiles Room 005. - See more at: http:\/\/www.cc.gatech.edu\/events\/arc-colloquium-and-joint-aco-student-seminar-peter-winkler#sthash.bjAYe3Eq.dpufPeter Winkler will be giving a joint ACR Colloquium and ACO Student Seminar on January 16, 2015 at 1:00 pm in Skiles Room 005. - See more at: http:\/\/www.cc.gatech.edu\/events\/arc-colloquium-and-joint-aco-student-seminar-peter-winkler#sthash.bjAYe3Eq.dpufPeter Winkler will be giving a joint ACR Colloquium and ACO Student Seminar on January 16, 2015 at 1:00 pm in Skiles Room 005. - See more at: http:\/\/www.cc.gatech.edu\/events\/arc-colloquium-and-joint-aco-student-seminar-peter-winkler#sthash.mXKxEKom.dpufPeter Winkler will be giving a joint ACR Colloquium and ACO Student Seminar on January 16, 2015 at 1:00 pm in Skiles Room 005. - See more at: http:\/\/www.cc.gatech.edu\/events\/arc-colloquium-and-joint-aco-student-seminar-peter-winkler#sthash.mXKxEKom.dpuf","format":"limited_html"}],"field_summary_sentence":[{"value":"Peter Winkler will be giving a joint ACR Colloquium and ACO Student Seminar on January 16, 2015 at 1:00 pm in Skiles Room 005. - See more at: http:\/\/www.cc.gatech.edu\/events\/arc-colloquium-and-joint-aco-student-seminar-peter-winkler#sthash.bjAYe3Eq.d"}],"uid":"27466","created_gmt":"2015-01-02 10:11:25","changed_gmt":"2017-04-13 21:20:51","author":"Dani Denton","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2015-01-16T12:00:00-05:00","event_time_end":"2015-01-16T13:00:00-05:00","event_time_end_last":"2015-01-16T13:00:00-05:00","gmt_time_start":"2015-01-16 17:00:00","gmt_time_end":"2015-01-16 18:00:00","gmt_time_end_last":"2015-01-16 18:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[{"id":"111051","name":"Algorithm and Randomness Center"},{"id":"109","name":"Georgia Tech"},{"id":"1808","name":"graduate students"},{"id":"113281","name":"Peter Winkler"},{"id":"14673","name":"theory"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1789","name":"Conference\/Symposium"}],"invited_audience":[{"id":"78751","name":"Undergraduate students"},{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EDani Denton\u003C\/p\u003E\u003Cp\u003Edenton at cc dot gatech dot edu\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"374251":{"#nid":"374251","#data":{"type":"event","title":"ARC Colloquium\/ML Seminar series: Elad Hazan - Princeton University","body":[{"value":"\u003Cp align=\u0022center\u0022\u003E(Please note that the talk will be held in MiRC 102 A \u0026amp; B and the refreshments will be served at the talk)\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp;\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EProjection-free Optimization\u0026nbsp;and Online Learning\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EModern large data sets prohibit any super-linear time operations. This motivates the study of iterative optimization algorithms with low complexity per iteration. The computational bottleneck in applying state-of-the-art iterative methods is many times the so-called \u0022projection step\u0022.\u003Cbr \/\u003EWe consider projection-free optimization\/learning that replaces projections by more efficient linear optimization steps. We describe the first linearly-converging algorithm of this type for polyhedral sets and how it gives rise to optimal-rate stochastic optimization and online learning algorithms.\u003Cbr \/\u003E\u003Cbr \/\u003E\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Elad Hazan presents a talk as part of the ARC Colloquium series and co-sponsored by the Machine Learning Seminar Series"}],"uid":"27466","created_gmt":"2015-02-06 17:45:07","changed_gmt":"2017-04-13 21:20:08","author":"Dani Denton","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2015-03-25T15:00:00-04:00","event_time_end":"2015-03-25T16:00:00-04:00","event_time_end_last":"2015-03-25T16:00:00-04:00","gmt_time_start":"2015-03-25 19:00:00","gmt_time_end":"2015-03-25 20:00:00","gmt_time_end_last":"2015-03-25 20:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"47223","name":"College of Computing"},{"id":"50875","name":"School of Computer Science"},{"id":"70263","name":"ARC"}],"categories":[],"keywords":[{"id":"111051","name":"Algorithm and Randomness Center"},{"id":"4265","name":"ARC"},{"id":"9267","name":"ARC Colloquium"},{"id":"9167","name":"machine learning"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78751","name":"Undergraduate students"},{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EDani Denton\u003C\/p\u003E\u003Cp\u003Edenton at cc dot gatech dot edu\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"380871":{"#nid":"380871","#data":{"type":"event","title":"ARC Colloquium: Nikhil Devanur - Microsoft Research","body":[{"value":"\u003Cp align=\u0022center\u0022\u003E(Refreshments will be served in Klaus 2222 at 2 pm)\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp;\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EOnline Advertisements and Online Algorithms\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003ECapacity or budget planning is an important component of any online ad serving platform. This has given rise to a rich and exciting line of work in online algorithms, and one of the most successful marriages of theory and practice. The practical aspects have directly influenced the theory and the theory has had significant impact on the design of modern advertising systems. The talk will give an overview of this interaction and some recent results on a very general problem called the online convex programming problem.\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003ENikhil R. Devanur is a researcher in the Theory group at Microsoft Research, Redmond. He is interested in designing algorithms that are faster, simpler, work online or in a distributed fashion, for some of the fundamental combinatorial optimization problem and in \u0022Automated Economics\u0022,\u0026nbsp; which studies the question of how technology can be used to improve the efficiency of economic systems. Prior to joining Microsoft Research, Nikhil got his PhD from Georgia Tech and spent a year at the Toyota Technological Institute at Chicago as a Research Assistant Professor.\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Nikhil Devanur presents a talk as part of the ARC Colloquium series."}],"uid":"27466","created_gmt":"2015-02-23 11:04:30","changed_gmt":"2017-04-13 21:19:59","author":"Dani Denton","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2015-04-13T14:00:00-04:00","event_time_end":"2015-04-13T15:00:00-04:00","event_time_end_last":"2015-04-13T15:00:00-04:00","gmt_time_start":"2015-04-13 18:00:00","gmt_time_end":"2015-04-13 19:00:00","gmt_time_end_last":"2015-04-13 19:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"related_links":[{"url":"http:\/\/www.arc.gatech.edu\/","title":"Algorithms \u0026 Randomness Center (ARC)"}],"groups":[{"id":"47223","name":"College of Computing"},{"id":"50877","name":"School of Computational Science and Engineering"},{"id":"70263","name":"ARC"}],"categories":[],"keywords":[{"id":"111051","name":"Algorithm and Randomness Center"},{"id":"4265","name":"ARC"},{"id":"9267","name":"ARC Colloquium"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78751","name":"Undergraduate students"},{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EDani Denton\u003C\/p\u003E\u003Cp\u003Edenton at cc dot gatech dot edu\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"386111":{"#nid":"386111","#data":{"type":"event","title":"ARC Colloquium: Anup Rao - Yale University","body":[{"value":"\u003Cp\u003E(Refreshments will be served in Klaus 2222 at 2 pm)\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E \u003Cbr \/\u003EAlgorithms for Lipschitz Learning on Graphs\u003Cbr \/\u003E\u003Cbr \/\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E \u003Cbr \/\u003EWe develop fast algorithms for solving regression problems on graphs where one is given the value of a function at some vertices, and must find its smoothest possible extension to all vertices. The extension we compute is the absolutely minimal Lipschitz extension, and is the limit for large p of p-Laplacian regularization. We present an algorithm that computes a minimal Lipschitz extension in expected linear time, and an algorithm that computes an absolutely minimal Lipschitz extension in expected time O(mn). The latter algorithm has variants that seem to run much faster in practice. These extensions are particularly amenable to regularization: we can perform l_0 regularization on the given values in polynomial time and l_1 regularization on the graph edge weights in time O(m^(3\/2)). Our algorithms naturally extend to directed graphs.\u0026nbsp; This is a joint work with Rasmus Kyng, Sushant Sachdeva and Daniel Spielman.\u003Cbr \/\u003E\u003Cbr \/\u003E\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Anup Rao presents a talk as part of the ARC Colloquium series."}],"uid":"27466","created_gmt":"2015-03-09 16:57:38","changed_gmt":"2017-04-13 21:19:47","author":"Dani Denton","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2015-03-30T14:00:00-04:00","event_time_end":"2015-03-30T15:00:00-04:00","event_time_end_last":"2015-03-30T15:00:00-04:00","gmt_time_start":"2015-03-30 18:00:00","gmt_time_end":"2015-03-30 19:00:00","gmt_time_end_last":"2015-03-30 19:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"related_links":[{"url":"http:\/\/www.arc.gatech.edu\/","title":"Algorithms \u0026 Randomness Center (ARC)"},{"url":"https:\/\/www.google.com\/maps\/place\/Klaus+Advanced+Computing+Building\/@33.777252,-84.396185,17z\/data=!3m1!4b1!4m2!3m1!1s0x87b781ec0ab42ea5:0x16eec927f37b40ec","title":"GA Tech, Klaus Building, Room 1116 West"}],"groups":[{"id":"47223","name":"College of Computing"},{"id":"50875","name":"School of Computer Science"},{"id":"70263","name":"ARC"}],"categories":[],"keywords":[{"id":"112751","name":"(ARC)"},{"id":"114981","name":"Adaptive Data Analysis"},{"id":"111051","name":"Algorithm and Randomness Center"},{"id":"115001","name":"Computational Complexity"},{"id":"114991","name":"Computational Learning Theory"},{"id":"109","name":"Georgia Tech"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78751","name":"Undergraduate students"},{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EDani Denton\u003C\/p\u003E\u003Cp\u003Edenton at cc dot gatech dot edu\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"393021":{"#nid":"393021","#data":{"type":"event","title":"ARC 7 (Annual Event) with Keynote by Christos Papadimitriou","body":[{"value":"\u003Cp class=\u0022p1\u0022\u003E\u003Cstrong\u003ESchedule\u003C\/strong\u003E:\u003C\/p\u003E\u003Cp class=\u0022p1\u0022\u003E\u0026nbsp;9:00 - 9:05\u0026nbsp; \u0026nbsp; \u0026nbsp; Introduction\u003C\/p\u003E\u003Cp class=\u0022p1\u0022\u003E\u0026nbsp;9:05 - 10:35 \u0026nbsp; \u0026nbsp;Talks by \u003Cstrong\u003ESrinivas Aluru\u003C\/strong\u003E (CSE),\u003Cstrong\u003E\u003Cstrong\u003E Santosh Vempala\u003C\/strong\u003E (CS), \u003C\/strong\u003Eand\u003Cstrong\u003E Natashia Boland\u003C\/strong\u003E (ISyE)\u0026nbsp; (30 minutes each)\u003C\/p\u003E\u003Cp class=\u0022p1\u0022\u003E\u0026nbsp;10:35 - 11:00\u0026nbsp; Break and light snacks\u003C\/p\u003E\u003Cp class=\u0022p1\u0022\u003E\u0026nbsp;11:00 - 12:00\u0026nbsp; Keynote by \u003Cstrong\u003EChristos Papadimitriou\u003C\/strong\u003E (U.C.- Berkeley)\u0026nbsp;\u003C\/p\u003E\u003Cp class=\u0022p1\u0022\u003E(see titles and abstracts below)\u003C\/p\u003E\u003Cp class=\u0022p4\u0022\u003E\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ESrinivas Aluru, (CSE)\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ETitle: \u003C\/strong\u003EParallel machine learning approaches for reverse engineering genome-scale networks\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003EReverse engineering whole-genome networks from large-scale gene expression measurements and analyzing them to extract biologically valid hypotheses are important challenges in systems biology. While simpler models easily scale to large number of genes and gene expression datasets, more accurate models are compute intensive limiting their scale of applicability. In this talk, I will present our research on the development of parallel mutual information and Bayesian network based structure learning methods to eliminate such bottlenecks and facilitate genome-scale network structure learning.\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003E\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ESantosh Vempala, (CS)\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ETitle: \u003C\/strong\u003ESafe and Easy: Humanly Usable Password Generation Methods\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003EOn a typical day, humans brush teeth, read, eat, converse ... and type passwords. This last task seems to be overly time-consuming (multiple attempts, frequent resets) and insecure --- passwords are often compromised. We desire passwords that are HUMANLY USABLE, i.e., easy to generate when needed, and SECURE, i.e., any single password is hard to crack, but even knowing several passwords doesn\u0027t allow an adversary infer others. Is this possible? How? How to even measure human effort? These questions lead us to ask what (protocols and algorithms) humans can compute and cannot compute. We present a model for measuring the complexity of human computation, and apply it in a rigorous framework for password generation.\u003C\/p\u003E\u003Cp\u003EThis is joint work with Manuel Blum.\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ENatashia L Boland, (ISyE)\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E Alternating Projection Algorithms and Integer Programming\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E Alternating projection algorithms have been independently discovered, and have made a significant impact, in diverse areas of science and engineering. They remain of great interest and current activity in convex optimization, and were independently discovered for general-purpose integer programming (IP) in 2005. Their use has been one component of the major advances in IP technology that now make IP a valuable and practical tool for solution of large-scale industrial problems. An essential element of the success of these methods is the application of randomization within the alternating projection framework.\u0026nbsp; Since their first discovery for IP, the methods have been improved and extended in a number of directions. In this talk, we will give an overview of recent activity in these methods, including two new ideas for improving their performance.\u003C\/p\u003E\u003Cp\u003E\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EKeynote Speaker\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EChristos H \u003C\/strong\u003E\u003Cstrong\u003EPapadimitriou, \u003C\/strong\u003E\u003Cstrong\u003EUC-Berkeley\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E Life under the lens\u003Cbr \/\u003E \u003Cbr \/\u003E \u003Cstrong\u003EAbstract:\u003C\/strong\u003E Applying the algorithmic point of view to the natural, life, and social sciences often results in unexpected insights and progress in central problems, a mode of research that has been described as ``the lens of computation.\u0027\u0027\u0026nbsp; I will focus on examples in the life sciences, from joint work with Erick Chastain, Costis Daskalakis, Adi Livnat, Umesh Vazirani, Santosh Vempala, and Albert Wu:\u0026nbsp; Evolution of a population through sexual reproduction can be rethought of as a repeated game between genes played through the multiplicative weight updates algorithm.\u0026nbsp; In an infinite population, when selection acts not on genes alone but on pairs of genes, fixation can take exponentially many generations.\u0026nbsp; And unsupervised learning of patterns can be achieved spontaneously and with high probability through a simple and neurally plausible primitive. \u003Cbr \/\u003E \u003Cbr \/\u003E \u003Cstrong\u003EBio:\u003C\/strong\u003E Christos H. Papadimitriou is the C. Lester Hogan Professor of Computer Science at UC-Berkeley.\u0026nbsp; Before joining Berkeley in 1996, he taught at Harvard, MIT, NTU Athens, Stanford, and UCSD.\u0026nbsp; He has written five textbooks and many articles on algorithms and complexity, and their applications to optimization, databases, control, AI, robotics, economics, game theory, the Internet, evolution, and brain science.\u0026nbsp; He holds a PhD from Princeton, and seven honorary doctorates.\u0026nbsp; He is a member of the National Academy of Sciences of the US, the American Academy of Arts and Sciences, and the National Academy of Engineering. He has also written three novels: \u201cTuring\u201d, \u201cLogicomix\u201d (with Apostolos Doxiadis) and \u201cIndependence\u201d (in Greek).\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThe Algorithms \u0026amp; Randomness Center presents the annual ARC Day with Keynote speaker Christos Papadimitriou of U.C. Berkeley, along with talks by Srinivas Aluru (CSE), Natashia Boland (ISyE) and Santosh Vempala (CS).\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Title:  Life Under the Lens"}],"uid":"27466","created_gmt":"2015-04-01 17:41:12","changed_gmt":"2017-04-13 21:19:34","author":"Dani Denton","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2015-04-17T10:00:00-04:00","event_time_end":"2015-04-17T13:00:00-04:00","event_time_end_last":"2015-04-17T13:00:00-04:00","gmt_time_start":"2015-04-17 14:00:00","gmt_time_end":"2015-04-17 17:00:00","gmt_time_end_last":"2015-04-17 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"47223","name":"College of Computing"},{"id":"50875","name":"School of Computer Science"},{"id":"70263","name":"ARC"}],"categories":[],"keywords":[{"id":"111051","name":"Algorithm and Randomness Center"},{"id":"4265","name":"ARC"},{"id":"109","name":"Georgia Tech"},{"id":"1808","name":"graduate students"},{"id":"14673","name":"theory"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78751","name":"Undergraduate students"},{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EDani Denton\u003C\/p\u003E\u003Cp\u003E\u003Ca href=\u0022mailto:denton@cc.gatech.edu\u0022\u003Edenton@cc.gatech.edu\u003C\/a\u003E\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"421151":{"#nid":"421151","#data":{"type":"event","title":"ARC 6 \/ SCS Distinguished Lecture by Shafi Goldwasser","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003EEvent Schedule\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;1:00 - 1:30\u0026nbsp; :\u0026nbsp;\u003Ca href=\u0022http:\/\/www.arc.gatech.edu\/sites\/arc.gatech.edu\/files\/ARC6_Abstract_MattBaker_0.pdf\u0022\u003EMatt Baker\u003C\/a\u003E\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;1:30 - 2:00\u0026nbsp; :\u0026nbsp;\u003Ca href=\u0022http:\/\/www.arc.gatech.edu\/sites\/arc.gatech.edu\/files\/ARC6_Abstract_OzlemErgun.pdf\u0022\u003EOzlem Ergun\u003C\/a\u003E\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;2:00 - 2:30\u0026nbsp; :\u0026nbsp;\u003Ca href=\u0022http:\/\/www.arc.gatech.edu\/sites\/arc.gatech.edu\/files\/ARC6_Abstract_LanceFortnow.pdf\u0022\u003ELance Fortnow\u003C\/a\u003E\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;2:30 - 3:00\u0026nbsp; : Break\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;3:00 - 4:00\u0026nbsp; :\u0026nbsp;\u003Ca href=\u0022http:\/\/www.arc.gatech.edu\/sites\/arc.gatech.edu\/files\/ARC6_Abstract_ShafiGoldwasser.pdf\u0022\u003EShafi Goldwasser\u003C\/a\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u0026nbsp;The\u0026nbsp;Cryptographic\u0026nbsp;Lens\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EGoing beyond the basic challenge of private\u0026nbsp;communication, over the last 35 years\u0026nbsp;cryptography\u0026nbsp;has become the general study of correctness and privacy of\u0026nbsp;computation\u0026nbsp;in the presence of a computationally bounded adversary, and as such it has changed how we think about proofs, reductions, randomness, secrets, and information.\u003C\/p\u003E\u003Cp\u003EIn this talk I will discuss some beautiful developments in the theory of computing through this\u0026nbsp;cryptographic\u0026nbsp;lens, and the role\u0026nbsp;cryptography\u0026nbsp;can play in the next successful shift from local to global computation.\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EBio\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EShafi Goldwasser is the RSA Professor of Electrical Engineering and Computer Science in MIT, a co-leader of the cryptography and information security group and a member of the complexity theory group within the Theory of Computation Group and the Computer Science and Artificial Intelligence Laboratory.\u003Cbr \/\u003E\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u003Cem\u003EARC 6 Workshop \u0026amp; School of Computer Science Distinguished Lecture by Shafi Goldwasser, RSA Professor of Electrical Engineering and Computer Science, MIT - Computer Science and Artificial Intelligence Laboratory with additional talks by Matt Baker, Ozlem Ergun and Lance Fortnow.\u003C\/em\u003E\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"ARC 6 Workshop with Keynote Speaker Shafi Goldwasser"}],"uid":"27466","created_gmt":"2015-07-02 14:06:08","changed_gmt":"2017-04-13 21:19:09","author":"Dani Denton","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2013-11-05T12:00:00-05:00","event_time_end":"2013-11-05T15:00:00-05:00","event_time_end_last":"2013-11-05T15:00:00-05:00","gmt_time_start":"2013-11-05 17:00:00","gmt_time_end":"2013-11-05 20:00:00","gmt_time_end_last":"2013-11-05 20:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[{"id":"111051","name":"Algorithm and Randomness Center"},{"id":"4265","name":"ARC"},{"id":"109","name":"Georgia Tech"},{"id":"1808","name":"graduate students"},{"id":"14673","name":"theory"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78751","name":"Undergraduate students"},{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003Edenton at cc dot gatech dot edu\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"436081":{"#nid":"436081","#data":{"type":"event","title":"ARC Colloquium: Andreas Galanis - University of Oxford","body":[{"value":"\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC) Colloquium\u003C\/strong\u003E\u003C\/p\u003E\u003Ch2 align=\u0022center\u0022\u003EAndreas Galanis\u0026nbsp;\u2013\u0026nbsp;University of Oxford\u003C\/h2\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EWednesday, August 26, 2015\u003C\/strong\u003E\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EKlaus 2447 - 2:00 pm\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003E\u0026nbsp;Title:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003ESwendsen-Wang Algorithm on the Mean-Field Potts Model\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EThis talk will focus on the q-state ferromagnetic Potts model on the n-vertex complete graph known as the mean-field (Curie-Weiss) model. We analyze the Swendsen-Wang algorithm which is a Markov chain that utilizes the random cluster representation for the ferromagnetic Potts model to recolor large sets of vertices in one step and potentially overcomes obstacles that inhibit single-site Glauber dynamics.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;The case q=2 (the Swendsen-Wang algorithm for the ferromagnetic Ising model) undergoes a slow-down at a critical temperature beta=betac (Long et al., 2014), but yet still has polynomial mixing time at all (inverse) temperatures beta\u0026gt;0 (Cooper et al., 2000).\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;In contrast, for q\u0026gt;=3 there are two critical temperatures 0\u0026lt;betau\u0026lt;betarc that are relevant (these correspond to phase transitions on the infinite tree). We prove that the mixing time of the Swendsen-Wang algorithm for the ferromagnetic Potts model on the n-vertex complete graph satisfies:\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E(i) O(log n) for beta\u0026lt;betau, (ii) O(n^{1\/3}) for beta=betau, (iii) exp(n^(Omega(1))) for betau\u0026lt;beta\u0026lt;betarc, and (iv) O(log n) for beta\u0026gt;=betarc.\u0026nbsp;These results complement refined results of Cuff et al. (2012) on the mixing time of the Glauber dynamics for the ferromagnetic Potts model.\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;The most interesting aspect of our analysis is at the critical temperature beta=betau, which requires a delicate choice of a potential function to balance the conflating factors for the slow drift away from a fixed point (which is repulsive but not Jacobian repulsive): close to the fixed point the variance from the percolation step dominates and sufficiently far from the fixed point the dynamics of the size of the dominant color class takes over.\u003C\/p\u003E\u003Cp\u003EJoint work with Daniel Stefankovic and Eric Vigoda.\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Klaus 2447 at 4 pm (Note: time and location are different than usual)"}],"uid":"27466","created_gmt":"2015-08-18 13:42:48","changed_gmt":"2017-04-13 21:18:45","author":"Dani Denton","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2015-08-26T15:05:00-04:00","event_time_end":"2015-08-26T16:00:00-04:00","event_time_end_last":"2015-08-26T16:00:00-04:00","gmt_time_start":"2015-08-26 19:05:00","gmt_time_end":"2015-08-26 20:00:00","gmt_time_end_last":"2015-08-26 20:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"47223","name":"College of Computing"},{"id":"50875","name":"School of Computer Science"},{"id":"70263","name":"ARC"}],"categories":[],"keywords":[{"id":"112751","name":"(ARC)"},{"id":"111051","name":"Algorithm and Randomness Center"},{"id":"115001","name":"Computational Complexity"},{"id":"114991","name":"Computational Learning Theory"},{"id":"109","name":"Georgia Tech"},{"id":"168064","name":"Swendsen-Wang algorithm"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78751","name":"Undergraduate students"},{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EDani Denton\u003C\/p\u003E\u003Cp\u003Edenton at cc dot gatech dot edu\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"436141":{"#nid":"436141","#data":{"type":"event","title":"ARC Colloquium Joint with ACO: Richard Peng - Georgia Tech","body":[{"value":"\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC) and ACO Joint \u0026nbsp;Colloquium\u003C\/strong\u003E\u003C\/p\u003E\u003Ch2 align=\u0022center\u0022\u003ERichard Peng\u0026nbsp;\u2013\u0026nbsp;Georgia Tech\u003C\/h2\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EMonday, August 31, 2015\u003C\/strong\u003E\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 East \u0026amp; West - 1:00 pm\u003C\/strong\u003E\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003E(Refreshments will be served in Klaus 2222 at 2 pm)\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EAlgorithm Frameworks Based on Structure Preserving Sampling\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003ESampling is a widely used algorithmic tool: running routines on a small representative subset of the data often leads to speedups while preserving accuracy. Recent works on algorithmic frameworks that relied on sampling graphs and matrices highlighted several connections between graph theory, statistics, optimization, and functional analysis. This talk will describe some key ideas that emerged from these connections:\u003C\/p\u003E\u003Cp\u003E*\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; Sampling as a generalized divide-and-conquer paradigm.\u003C\/p\u003E\u003Cp\u003E*\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; Implicit sampling without constructing the larger data set, and its algorithmic applications.\u003C\/p\u003E\u003Cp\u003E*\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; What does sampling need to preserve? What can sampling preserve?\u003C\/p\u003E\u003Cp\u003EThese ideas have applications in solvers for structured linear systems, network flow algorithms, input-sparsity time numerical routines, coresets, and dictionary learning.\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Klaus 1116 East \u0026 West at 1 pm"}],"uid":"27466","created_gmt":"2015-08-18 14:16:04","changed_gmt":"2017-04-13 21:18:45","author":"Dani Denton","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2015-08-31T14:00:00-04:00","event_time_end":"2015-08-31T15:00:00-04:00","event_time_end_last":"2015-08-31T15:00:00-04:00","gmt_time_start":"2015-08-31 18:00:00","gmt_time_end":"2015-08-31 19:00:00","gmt_time_end_last":"2015-08-31 19:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"47223","name":"College of Computing"},{"id":"50875","name":"School of Computer Science"},{"id":"70263","name":"ARC"}],"categories":[],"keywords":[{"id":"111051","name":"Algorithm and Randomness Center"},{"id":"4265","name":"ARC"},{"id":"115001","name":"Computational Complexity"},{"id":"114991","name":"Computational Learning Theory"},{"id":"109","name":"Georgia Tech"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78751","name":"Undergraduate students"},{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EDani Denton\u003C\/p\u003E\u003Cp\u003Edenton at cc dot gatech dot edu\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"438131":{"#nid":"438131","#data":{"type":"event","title":"ARC Colloquium: Charilaos Efthymiou - Georgia Tech","body":[{"value":"\u003Cp\u003ENote: Talk will be held in Marcus 1117-1118.\u003C\/p\u003E\u003Ch6 align=\u0022center\u0022\u003E\u003Cstrong\u003E\u0026nbsp;Algorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/h6\u003E\u003Ch5 align=\u0022center\u0022\u003ECharilaos Efthymiou \u2013 Georgia Tech\u003C\/h5\u003E\u003Ch6 align=\u0022center\u0022\u003E\u003Cstrong\u003EMonday, September 14, 2015\u003C\/strong\u003E\u003C\/h6\u003E\u003Ch6 align=\u0022center\u0022\u003E\u003Cstrong\u003EMarcus 1117 \u0026amp; 1118 - 1:00 pm\u003C\/strong\u003E\u003C\/h6\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003E(Refreshments will be served in Klaus 2222 at 2 pm)\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EReconstruction thresholds for the random colourings of G(n,m)\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EIn this talk we consider the reconstruction problem for the random colourings of a random graph G(n,m) of\u0026nbsp; degree d.\u003C\/p\u003E\u003Cp\u003EFor some k-colourable graph G,\u0026nbsp; the reconstruction problem studies the correlation between the assignment of a single vertex in G and that of its neighbours at distance r, under the uniform measure over the k-colourings of G. This is point to set correlation.\u003C\/p\u003E\u003Cp\u003EWhen the correlation persists as r grows, then we have reconstruction, otherwise we have non-reconstruction.\u003C\/p\u003E\u003Cp\u003EIt has been conjecture from statistical physics that for typical instances of G(n,m)\u0026nbsp; the transition from non-reconstruction to reconstruction exhibits a threshold behavior. That is, there is a critical value k_0, which depends on the expected degree d, such that the following is true:\u0026nbsp; When k\u0026gt;k_0 there is non-reconstruction while when k\u0026lt;k_0 there is reconstruction.\u003C\/p\u003E\u003Cp\u003EThe aforementioned phase transition has been related to the performance of local search algorithms as well as the shattering phenomenon in the solution space of the k-colourings.\u003C\/p\u003E\u003Cp\u003EIn this talk I discuss our recent results which show that the phase transition from statistical physics is indeed correct. Moreover, the point where this phase transition occurs, up to smaller order terms, is exactly at the point where it has been conjectured to be.\u003C\/p\u003E\u003Cp\u003EThe first step in our approach is to show that the Gibbs distribution over the k-colouring of G(n,m) converges locally to the Gibbs distribution over the k-colourings of a Poisson(d) Galton-Watson tree\u0026nbsp; T(d), for a wide range of\u0026nbsp; k. This allows to reduce our initial problem to studying the reconstruction on T(d). The second step is to establish the reconstruction threshold for the colourings of T(d).\u003C\/p\u003E\u003Cp\u003EThis talk is based on 2 recent works of mine.\u0026nbsp; One of them is a joint work with Amin Coja-Oghlan and Nor Jaafari.\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Marcus 1117 \u0026 1118 at 1 pm (Note: different location)"}],"uid":"27466","created_gmt":"2015-08-20 15:28:05","changed_gmt":"2017-04-13 21:18:39","author":"Dani Denton","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2015-09-14T14:00:00-04:00","event_time_end":"2015-09-14T15:00:00-04:00","event_time_end_last":"2015-09-14T15:00:00-04:00","gmt_time_start":"2015-09-14 18:00:00","gmt_time_end":"2015-09-14 19:00:00","gmt_time_end_last":"2015-09-14 19:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"related_links":[{"url":"http:\/\/www.arc.gatech.edu\/","title":"Algorithms \u0026 Randomness Center (ARC)"}],"groups":[{"id":"47223","name":"College of Computing"},{"id":"50875","name":"School of Computer Science"},{"id":"70263","name":"ARC"}],"categories":[],"keywords":[{"id":"111051","name":"Algorithm and Randomness Center"},{"id":"4265","name":"ARC"},{"id":"115001","name":"Computational Complexity"},{"id":"114991","name":"Computational Learning Theory"},{"id":"109","name":"Georgia Tech"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78751","name":"Undergraduate students"},{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EDani Denton\u003Cbr \/\u003Edenton at cc dot gatech dot edu\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"438751":{"#nid":"438751","#data":{"type":"event","title":"ARC Colloquium: Christine Heitsch - Georgia Tech","body":[{"value":"\u003Ch2 align=\u0022center\u0022\u003EChristine Heitsch \u2013 Georgia Tech\u003C\/h2\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EMonday, September 21, 2015\u003C\/strong\u003E\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 W - 1:00 pm\u003C\/strong\u003E\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003E(\u003C\/strong\u003E\u003Cstrong\u003ERefreshments will be served in Klaus 2222 at 2 pm)\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003Cstrong\u003ETitle: \u0026nbsp;\u0026nbsp; \u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EStrings, Trees, and RNA Folding\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EAn RNA molecule is a linear biochemical chain which folds into a three dimensional structure via a set of 2D base pairings known as a nested secondary structure.\u0026nbsp; Reliably determining a secondary structure for large RNA molecules, such as the genomes of most viruses, is an important open problem in molecular biology.\u0026nbsp; Using strings and (plane) trees as a combinatorial model of RNA folding, we give mathematical results which yield insights into RNA branching configurations and suggest new directions in understanding the structure of RNA viruses.\u0026nbsp; We also demonstrate that, under a suitable abstraction, complex biological problems can reveal surprising mathematical structure.\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Klaus 1116 West at 1 pm"}],"uid":"27466","created_gmt":"2015-08-21 17:21:41","changed_gmt":"2017-04-13 21:18:38","author":"Dani Denton","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2015-09-21T14:00:00-04:00","event_time_end":"2015-09-21T15:00:00-04:00","event_time_end_last":"2015-09-21T15:00:00-04:00","gmt_time_start":"2015-09-21 18:00:00","gmt_time_end":"2015-09-21 19:00:00","gmt_time_end_last":"2015-09-21 19:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"47223","name":"College of Computing"},{"id":"50875","name":"School of Computer Science"},{"id":"70263","name":"ARC"}],"categories":[],"keywords":[{"id":"111051","name":"Algorithm and Randomness Center"},{"id":"4265","name":"ARC"},{"id":"115001","name":"Computational Complexity"},{"id":"114991","name":"Computational Learning Theory"},{"id":"109","name":"Georgia Tech"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78751","name":"Undergraduate students"},{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EDani Denton\u003Cbr \/\u003Edenton at cc dot gatech dot edu\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"438761":{"#nid":"438761","#data":{"type":"event","title":"ARC Colloquium: Nicole Immorlica - Microsoft Research New England","body":[{"value":"\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC) \u003C\/strong\u003E\u003C\/p\u003E\u003Ch2 align=\u0022center\u0022\u003ENicole Immorlica - Microsoft Research New England\u003C\/h2\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EMonday, November 2, 2015\u003C\/strong\u003E\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 West \u2013 1:00 pm\u003C\/strong\u003E\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003E(Refreshments will be served in Klaus 2222 at 2 pm)\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ETitle: \u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EThe Emergent Structure of Simple Behaviors in Complex Networks\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EMany games of social significance are played in a networked context.\u0026nbsp; In these settings, agents often exhibit simple behaviors, shaped by local preferences and social norms.\u0026nbsp; The interplay of these behaviors and the underlying network give rise to emergent structures with global impact.\u0026nbsp; In this talk, we explore the impact of networked behavior on social capital, segregation, and learning.\u003C\/p\u003E\u003Cp\u003EFirst we study the emergence of social capital in dynamic, anonymous social networks, such as online communities.\u0026nbsp; We find that, despite the lack of punitive strategies, (partial) cooperation is sustainable at an intuitive and simple equilibrium as cooperation allows an individual to interact with an increasing number of other cooperators, resulting in the formation of valuable social capital.\u003C\/p\u003E\u003Cp\u003ENext we examine the emergence of segregation in geographical networks.\u0026nbsp; In 1969, Schelling introduced a model of racial segregation in which individuals move out of neighborhoods where their ethnicity constitutes a minority and suggested that this local behavior can cause global segregation effects. Our rigorous analysis shows that, in contrast to prior interpretations, the outcome exhibits local but not global segregation.\u003C\/p\u003E\u003Cp\u003EFinally, we study learning outcomes in social networks. Individuals with independent opinions asynchronously update their declared opinion to match the majority report of their neighbors.\u0026nbsp; We show that the population will converge to the majority opinion with high probability if the underlying network is large, sparse, and expansive, properties reflected by realistic social networks.\u003C\/p\u003E\u003Cp\u003EBased on joint works with Christie Brandt, Michal Feldman, Gautam Kamath, Robert Kleinberg, Brendan Lucier, Brian Rogers and Matt Weinberg.\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Klaus 1116 West at 1 pm"}],"uid":"27466","created_gmt":"2015-08-21 17:25:36","changed_gmt":"2017-04-13 21:18:38","author":"Dani Denton","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2015-11-02T12:00:00-05:00","event_time_end":"2015-11-02T13:00:00-05:00","event_time_end_last":"2015-11-02T13:00:00-05:00","gmt_time_start":"2015-11-02 17:00:00","gmt_time_end":"2015-11-02 18:00:00","gmt_time_end_last":"2015-11-02 18:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[{"id":"111051","name":"Algorithm and Randomness Center"},{"id":"4265","name":"ARC"},{"id":"115001","name":"Computational Complexity"},{"id":"114991","name":"Computational Learning Theory"},{"id":"109","name":"Georgia Tech"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78751","name":"Undergraduate students"},{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EDani Denton\u003Cbr \/\u003Edenton at cc dot gatech dot edu\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"440601":{"#nid":"440601","#data":{"type":"event","title":"SIAM Conference on Discrete Mathematics","body":[{"value":"\u003Cp\u003E\u003Ca href=\u0022http:\/\/www.siam.org\/meetings\/dm16\/index.php\u0022 title=\u0022http:\/\/www.siam.org\/meetings\/dm16\/index.php\u0022\u003Ehttp:\/\/www.siam.org\/meetings\/dm16\/index.php\u003C\/a\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EOrganizing Committee Co-Chairs\u003C\/strong\u003E\u003Cbr \/\u003E Henry Cohn, Microsoft Research New England, USA\u003Cbr \/\u003E Dana Randall, Georgia Institute of Technology, USA\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Georgia State University: http:\/\/www.siam.org\/meetings\/dm16\/index.php"}],"uid":"27466","created_gmt":"2015-08-26 11:39:38","changed_gmt":"2017-04-13 21:18:32","author":"Dani Denton","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2016-06-06T09:00:00-04:00","event_time_end":"2016-06-10T18:00:00-04:00","event_time_end_last":"2016-06-10T18:00:00-04:00","gmt_time_start":"2016-06-06 13:00:00","gmt_time_end":"2016-06-10 22:00:00","gmt_time_end_last":"2016-06-10 22:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"related_links":[{"url":"http:\/\/www.siam.org\/meetings\/dm16\/index.php","title":"SIAM Conference on Discrete Mathematics"}],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[{"id":"10467","name":"Dana Randall"},{"id":"10176","name":"discrete mathematics"},{"id":"168079","name":"SIAM Conference"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78751","name":"Undergraduate students"},{"id":"78761","name":"Faculty\/Staff"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022http:\/\/www.siam.org\/meetings\/dm16\/\u0022 title=\u0022http:\/\/www.siam.org\/meetings\/dm16\/\u0022\u003Ehttp:\/\/www.siam.org\/meetings\/dm16\/\u003C\/a\u003E\u003C\/p\u003E\u003Cp\u003EPosted by Dani Denton\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"444651":{"#nid":"444651","#data":{"type":"event","title":"ARC Colloquium: Dan Gusfield - UC Davis","body":[{"value":"\u003Cp\u003EPlease note: talk is at 4 pm on Wednesday.\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u0026nbsp;\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\u003Ch2 align=\u0022center\u0022\u003EDan Gusfield - UC Davis\u003C\/h2\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EWednesday, September 9, 2015\u003C\/strong\u003E\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 West - 4:00 pm\u003C\/strong\u003E\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003E(Refreshments will be served in 1116W at 4 pm)\u003C\/strong\u003E\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EPhylogenetics Through the Lens of Chordal Graph Theory\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EThe evolutionary history of a set of species is generally described by a hylogenetic tree.\u0026nbsp; The combinatorial structure of phylogenetic trees is very well understood when biological characters can only take on two states. But, when characters can take on more than two states, the combinatorial structure is much less understood. The Multi-State Perfect Phylogeny (MPP) problem addresses the case of \u0026nbsp;non-binary states.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EThe MPP problem was initially defined (using different terminology) in a 1975 paper by Peter Buneman that establishes a deep relationship between the MPP problem and the class of graphs called chordal graphs. It showed a how to view the multi-state perfect phylogeny problem as a problem of triangulating non-chordal graphs. While that result has been used in mathematical results, it was not widely exploited as a computational tool.\u003C\/p\u003E\u003Cp\u003EIn this talk, I discuss our work on exploiting the chordal graph approach to solve and study multi-state perfect phylogeny and related problems.\u0026nbsp; I will discuss how the problem relates to minimal triangulation, 2-SAT, integer linear programming, and undirected tree compatibility.\u0026nbsp; I will also discuss generalizations of the classic four-gametes condition, which characterizes a binary (perfect) phylogeny, to conditions that characterize multi-state perfect phylogenies, and I will identify open questions in this field.\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EDan Gusfield of UC Davis will give a talk at the ARC Center Colloquium on Sept. 9 at 4 pm in Klaus 1116 West.\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Klaus 1116 West at 4 pm  (Note: different day and time.)"}],"uid":"27466","created_gmt":"2015-09-04 08:48:16","changed_gmt":"2017-04-13 21:18:23","author":"Dani Denton","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2015-09-09T17:00:00-04:00","event_time_end":"2015-09-09T18:00:00-04:00","event_time_end_last":"2015-09-09T18:00:00-04:00","gmt_time_start":"2015-09-09 21:00:00","gmt_time_end":"2015-09-09 22:00:00","gmt_time_end_last":"2015-09-09 22:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"related_links":[{"url":"http:\/\/www.arc.gatech.edu\/","title":"Algorithms \u0026 Randomness Center (ARC)"}],"groups":[{"id":"47223","name":"College of Computing"},{"id":"50875","name":"School of Computer Science"},{"id":"70263","name":"ARC"}],"categories":[],"keywords":[{"id":"111051","name":"Algorithm and Randomness Center"},{"id":"4265","name":"ARC"},{"id":"115001","name":"Computational Complexity"},{"id":"114991","name":"Computational Learning Theory"},{"id":"109","name":"Georgia Tech"},{"id":"140451","name":"Phylogenetics Through the Lens of Chordal Graph Theory"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78751","name":"Undergraduate students"},{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EDani Denton\u003Cbr \/\u003Edenton at cc dot gatech dot edu\u003Cbr \/\u003E\u003Cbr \/\u003E\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"445161":{"#nid":"445161","#data":{"type":"event","title":"ARC\/ACO Colloquium: Alan Frieze - Carnegie Mellon University","body":[{"value":"\u003Cp\u003EPlease note the talk is at \u003Cstrong\u003E11 am\u003C\/strong\u003E in \u003Cstrong\u003E1116 East\u003C\/strong\u003E\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\u003Ch2 align=\u0022center\u0022\u003EAlan Frieze \u2013 Carnegie Mellon University\u003C\/h2\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EWednesday, September 23, 2015\u003C\/strong\u003E\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 E - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003E(Refreshments will be served in Klaus 2222 at Noon)\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003Cstrong\u003ETitle: \u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003ETitle: Probabilistic analysis of some combinatorial optimization problems.\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EWe consider the following probabilistic model. The edges of a (complete) graph have unknown random edge weights. We want to build a minimum cost structure. We can ask for the weight of an edge and then accept or reject the edge. Once rejected, the edge cannot be accepted later. We must accept enough edges to support a structure and we are charged for all the edges accepted, even if not used. We give results in this model for minimum spanning tree, perfect matching and shortest path.\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;Joint work with Colin Cooper and Wesley Pegden.\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Klaus 1116 East at 11 am  (Note: different day, time and location)"}],"uid":"27466","created_gmt":"2015-09-04 17:37:44","changed_gmt":"2017-04-13 21:18:22","author":"Dani Denton","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2015-09-23T12:00:00-04:00","event_time_end":"2015-09-23T13:00:00-04:00","event_time_end_last":"2015-09-23T13:00:00-04:00","gmt_time_start":"2015-09-23 16:00:00","gmt_time_end":"2015-09-23 17:00:00","gmt_time_end_last":"2015-09-23 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"related_links":[{"url":"http:\/\/www.math.cmu.edu\/~af1p\/","title":"Alan Frieze"},{"url":"http:\/\/www.arc.gatech.edu\/","title":"Algorithms \u0026 Randomness Center (ARC)"}],"groups":[{"id":"47223","name":"College of Computing"},{"id":"50875","name":"School of Computer Science"},{"id":"70263","name":"ARC"}],"categories":[],"keywords":[{"id":"111051","name":"Algorithm and Randomness Center"},{"id":"4265","name":"ARC"},{"id":"115001","name":"Computational Complexity"},{"id":"114991","name":"Computational Learning Theory"},{"id":"109","name":"Georgia Tech"},{"id":"140651","name":"Probabilistic Combinatorics"},{"id":"140661","name":"Theoretical Computer Science and Operations Research"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78751","name":"Undergraduate students"},{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EDani Denton\u003Cbr \/\u003Edenton at cc dot gatech dot edu\u003Cbr \/\u003E\u003Cbr \/\u003E\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"446251":{"#nid":"446251","#data":{"type":"event","title":"ARC Colloquium: Anup Rao - Georgia Tech","body":[{"value":"\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC) \u003C\/strong\u003E\u003C\/p\u003E\u003Ch2 align=\u0022center\u0022\u003EAnup Rao \u2013 Georgia Tech\u003C\/h2\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EMonday, October 26, 2015\u003C\/strong\u003E\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 West \u2013 1:00 pm\u003C\/strong\u003E\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003E(Refreshments will be served in Klaus 2222 at 2 pm)\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ETitle: \u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EThe Stochastic Block Model and Communities in Sparse Random Graphs: Detection at Optimal Rate\u003Cbr \/\u003E \u003Cbr \/\u003E \u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EWe consider the problem of communities detection in sparse random graphs. Our model is the so-called Stochastic Block Model, which has been immensely popular in the recent statistics literature. Let X1,...Xk be vertex sets of size n each (where k is fixed and n is large). One draws random edges inside each Xi with probability a\/n, and between Xi and Xj with probability b\/n, for some constants a and b. Given one instance of this sparse random graph, our goal is to recover the sets Xi as correctly as possible. We are going to present a fast spectral algorithm which does this job at the optimal rate (namely the relation between a,b and the number of mistakes in the recovery is optimal). Our algorithm is based on spectral properties of random sparse matrices and is easy to implement. We will also discuss some related works with spectral algorithms and an open question concerning random matrices.\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Klaus 1116 West at 1 pm"}],"uid":"27466","created_gmt":"2015-09-10 09:44:12","changed_gmt":"2017-04-13 21:18:21","author":"Dani Denton","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2015-10-26T14:00:00-04:00","event_time_end":"2015-10-26T15:00:00-04:00","event_time_end_last":"2015-10-26T15:00:00-04:00","gmt_time_start":"2015-10-26 18:00:00","gmt_time_end":"2015-10-26 19:00:00","gmt_time_end_last":"2015-10-26 19:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"related_links":[{"url":"http:\/\/www.arc.gatech.edu\/","title":"Algorithms \u0026 Randomness Center (ARC)"}],"groups":[{"id":"47223","name":"College of Computing"},{"id":"50875","name":"School of Computer Science"},{"id":"70263","name":"ARC"}],"categories":[],"keywords":[{"id":"111051","name":"Algorithm and Randomness Center"},{"id":"4265","name":"ARC"},{"id":"115001","name":"Computational Complexity"},{"id":"114991","name":"Computational Learning Theory"},{"id":"109","name":"Georgia Tech"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78751","name":"Undergraduate students"},{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EDani Denton\u003Cbr \/\u003Edenton at cc dot gatech dot edu\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"446271":{"#nid":"446271","#data":{"type":"event","title":"ARC Colloquium: Yitong Yin \u2013 Nanjing University","body":[{"value":"\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC) \u003C\/strong\u003E\u003C\/p\u003E\u003Ch2 align=\u0022center\u0022\u003EYitong Yin \u2013 Nanjing University\u003C\/h2\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EMonday, September 28, 2015\u003C\/strong\u003E\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 West - 1:00 pm\u003C\/strong\u003E\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003E(Refreshments will be served in Klaus 2222 at 2 pm)\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ETitle: \u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003ECounting hypergraph matchings up to uniqueness threshold\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EWe study the problem of approximately counting hypergraph matchings with an activity parameter $\\lambda$ in hypergraphs of bounded maximum degree and bounded maximum size of hyperedges. This problem unifies two important statistical physics models in approximate counting: the hardcore model (graph independent sets) and the monomer-dimer model (graph matchings).\u003C\/p\u003E\u003Cp\u003EWe show for this model the critical activity $\\lambda_c= \\frac{d^d}{k (d-1)^{d+1}}$ is the threshold for the uniqueness of Gibbs measures on the infinite $(d+1)$-uniform $(k+1)$-regular hypertree. And we show that when $\\lambda\u0026lt;\\lambda_c$ the model exhibits strong spatial mixing at an exponential rate and there is an FPTAS for the partition function of the model on all hypergraphs of maximum degree at most $k+1$ and maximum \u0026nbsp;edge size at most $d+1$. Assuming NP$\\neq$RP, there is no FPRAS for the partition function of the model when $\\lambda \u0026gt; 2\\lambda_c$ on above family of hypergraphs .\u003C\/p\u003E\u003Cp\u003ETowards closing this gap and obtaining a tight transition of approximability, we study the local weak convergence from an infinite sequence of random finite hypergraphs to the infinite uniform regular hypertree with specified symmetry, and prove a surprising result: the existence of such local convergence is fully characterized by the reversibility of the uniform random walk on the infinite hypertree projected on the symmetry classes. We also give explicit constructions sequence of random finite hypergraphs with proper local convergence property when the reversibility condition is satisfied.\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Klaus 1116 West at 1 pm"}],"uid":"27466","created_gmt":"2015-09-10 09:47:51","changed_gmt":"2017-04-13 21:18:21","author":"Dani Denton","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2015-09-28T14:00:00-04:00","event_time_end":"2015-09-28T15:00:00-04:00","event_time_end_last":"2015-09-28T15:00:00-04:00","gmt_time_start":"2015-09-28 18:00:00","gmt_time_end":"2015-09-28 19:00:00","gmt_time_end_last":"2015-09-28 19:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"related_links":[{"url":"http:\/\/www.arc.gatech.edu\/","title":"Algorithms \u0026 Randomness Center (ARC)"}],"groups":[{"id":"47223","name":"College of Computing"},{"id":"50875","name":"School of Computer Science"},{"id":"70263","name":"ARC"}],"categories":[],"keywords":[{"id":"111051","name":"Algorithm and Randomness Center"},{"id":"4265","name":"ARC"},{"id":"115001","name":"Computational Complexity"},{"id":"114991","name":"Computational Learning Theory"},{"id":"109","name":"Georgia Tech"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78751","name":"Undergraduate students"},{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EDani Denton\u003Cbr \/\u003Edenton at cc dot gatech dot edu\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"448851":{"#nid":"448851","#data":{"type":"event","title":"ARC Colloquium: David P. Woodruff - IBM","body":[{"value":"\u003Ch2 align=\u0022center\u0022\u003EDavid P. Woodruff - IBM\u003C\/h2\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EMonday, November 9, 2015\u003C\/strong\u003E\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 West \u2013 1:00 pm\u003C\/strong\u003E\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003E(Refreshments will be served in Klaus 2222 at 2 pm)\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003Cstrong\u003ETitle: \u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EInput Sparsity Time Algorithms for Robust Regression and Robust Low Rank Approximation\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EWe give near optimal algorithms for regression and low rank approximation in the robust case. For regression, we give algorithms generalizing l_p regression to M-Estimator loss functions, such as the Huber measure, which enjoys the robustness properties of l_1 as well as the smoothness properties of l_2. For low rank approximation, we give new algorithms generalizing the singular value decomposition to sum of p-th powers of distances, and M-estimator loss functions applied to the distances. Some problems here are arguably even more fundamental than the SVD itself, such as given a set of points, find a line which minimizes the sum of distances of the points to the line, rather than the sum of squared distances. These measures are less sensitive to outliers and we show they can be computed approximately in time proportional to the number of non-zeros of the input matrix. We also discuss hardness results in the low rank approximation setting.\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Klaus 1116 West at 1 pm"}],"uid":"27466","created_gmt":"2015-09-16 14:39:24","changed_gmt":"2017-04-13 21:18:16","author":"Dani Denton","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2015-11-09T12:00:00-05:00","event_time_end":"2015-11-09T13:00:00-05:00","event_time_end_last":"2015-11-09T13:00:00-05:00","gmt_time_start":"2015-11-09 17:00:00","gmt_time_end":"2015-11-09 18:00:00","gmt_time_end_last":"2015-11-09 18:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[{"id":"111051","name":"Algorithm and Randomness Center"},{"id":"4265","name":"ARC"},{"id":"115001","name":"Computational Complexity"},{"id":"114991","name":"Computational Learning Theory"},{"id":"109","name":"Georgia Tech"},{"id":"1126","name":"ibm"},{"id":"9167","name":"machine learning"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78751","name":"Undergraduate students"},{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EDani Denton\u003Cbr \/\u003Edenton at cc dot gatech dot edu\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"449061":{"#nid":"449061","#data":{"type":"event","title":"ARC Colloquium: James Saunderson","body":[{"value":"\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EJames Saunderson - University of Washington\u003Cbr \/\u003E\u003C\/strong\u003E\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EMonday, November 23, 2015\u003Cbr \/\u003EKlaus 1116 West \u2013 1:00 pm\u003Cbr \/\u003E(Refreshments will be served in Klaus 2222 at 2 pm)\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ETitle: \u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003ESemidefinite descriptions of regular polygons (and beyond)\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003ESemidefinite programs are a family of convex optimization problems that generalize linear programs and can model a wide range of problems from areas as diverse as statistics, robotics, and combinatorial optimization. Despite this, understanding the expressive power and limitations of (small) semidefinite programs remains a significant challenge.\u003C\/p\u003E\u003Cp\u003EThis talk is centered on new efficient descriptions of regular polygons (and related polytopes) in terms of the feasible regions of semidefinite programs. These constructions, for instance, give the first known family of polytopes with semidefinite programming descriptions that are asymptotically smaller than the best linear programming descriptions.\u003C\/p\u003E\u003Cp\u003EBased on joint work with Hamza Fawzi (MIT) and Pablo Parrilo (MIT).\u003C\/p\u003E\u003Cp\u003EHost is Greg Blekherman (\u003Ca href=\u0022mailto:greg@math.gatech.edu\u0022\u003Egreg@math.gatech.edu\u003C\/a\u003E).\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Klaus 1116 West at 1 pm"}],"uid":"27466","created_gmt":"2015-09-17 11:26:14","changed_gmt":"2017-04-13 21:18:14","author":"Dani Denton","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2015-11-23T12:00:00-05:00","event_time_end":"2015-11-23T13:00:00-05:00","event_time_end_last":"2015-11-23T13:00:00-05:00","gmt_time_start":"2015-11-23 17:00:00","gmt_time_end":"2015-11-23 18:00:00","gmt_time_end_last":"2015-11-23 18:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"47223","name":"College of Computing"},{"id":"50875","name":"School of Computer Science"},{"id":"70263","name":"ARC"}],"categories":[],"keywords":[{"id":"111051","name":"Algorithm and Randomness Center"},{"id":"4265","name":"ARC"},{"id":"115001","name":"Computational Complexity"},{"id":"114991","name":"Computational Learning Theory"},{"id":"109","name":"Georgia Tech"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78751","name":"Undergraduate students"},{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EDani Denton\u003Cbr \/\u003Edenton at cc dot gatech dot edu\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"453411":{"#nid":"453411","#data":{"type":"event","title":"ARC Colloquium: Andrea Richa - Arizona State University","body":[{"value":"\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC) \u003C\/strong\u003E\u003C\/p\u003E\u003Ch2 align=\u0022center\u0022\u003EAndrea W. Richa \u2013 Arizona State University\u003C\/h2\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EFriday, October 9, 2015\u003C\/strong\u003E\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 East \u2013 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ETitle: \u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EProgrammable Matter: Self-organizing Particle Systems\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EFrom the level of chemical reaction networks within cells to the social structures of higher organisms, biological systems take advantage of distributed computation to perform a myriad of complex functions. Computer\u0026nbsp; scientists and engineers have investigated biological and physical systems in order to understand how these systems can provide us with the necessary insight to realize self-organizing systems of artificial, programmable particles. Those investigations led to the notion of programmable matter. The impact of programmable matter will be seen across all areas, from improved drugs and assistance in nano surgery, to increased productivity, greater capabilities in automation, etc. Fully distributed computation, self-organization and self-stabilization are key for the scalability and robustness of such systems. In this talk, we present a general abstract model for programmable matter consisting of systems of simple, computationally-limited particles. We present self-organizing algorithms for the problems of leader election, coating, and shape formation.\u003C\/p\u003E\u003Cp\u003EThis work has been done in collaboration with Zahra Derakhshandeh (ASU), Christian Scheideler, Robert Gmyr and Thim Strothmann (U. of Paderborn, Germany), and others.\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EAndrea W. Richa is an Associate Professor in Computer Science at Arizona State University (ASU), Tempe, AZ. She is also affiliated with the Biomimicry Center at ASU. She received her M.S. and Ph.D. degrees from the School of Computer Science at Carnegie Mellon University, in 1995 and 1998, respectively. Prof. Richa\u0027s work on distributed algorithms has been widely cited, and includes work on self-organizing particle systems, wireless network modeling and topology control, wireless jamming, data mule networks, underwater optical networking, distributed load balancing, and distributed hash tables (DHTs). Dr. Richa was the recipient of an NSF CAREER Award in 1999, is currently an Associate Editor of IEEE Transactions on Mobile Computing, and has served as keynote speaker and program\\general chair of several prestigious conferences. Dr. Richa is also a founding member of UON Technologies. For a selected list of her publications and other accomplishments, and current research projects, please visit \u003Ca href=\u0022http:\/\/www.public.asu.edu\/~aricha\u0022\u003Ewww.public.asu.edu\/~aricha\u003C\/a\u003E .\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Klaus 1116 East at 11:00 am"}],"uid":"27466","created_gmt":"2015-09-29 11:41:15","changed_gmt":"2017-04-13 21:18:06","author":"Dani Denton","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2015-10-09T12:00:00-04:00","event_time_end":"2015-10-09T13:00:00-04:00","event_time_end_last":"2015-10-09T13:00:00-04:00","gmt_time_start":"2015-10-09 16:00:00","gmt_time_end":"2015-10-09 17:00:00","gmt_time_end_last":"2015-10-09 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"related_links":[{"url":"http:\/\/www.arc.gatech.edu\/","title":"Algorithms \u0026 Randomness Center (ARC)"},{"url":"http:\/\/www.public.asu.edu\/~aricha","title":"Andrea W. Richa \u2013 Arizona State University"}],"groups":[{"id":"47223","name":"College of Computing"},{"id":"50875","name":"School of Computer Science"},{"id":"70263","name":"ARC"}],"categories":[],"keywords":[{"id":"111051","name":"Algorithm and Randomness Center"},{"id":"4265","name":"ARC"},{"id":"115001","name":"Computational Complexity"},{"id":"114991","name":"Computational Learning Theory"},{"id":"109","name":"Georgia Tech"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78751","name":"Undergraduate students"},{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EDani Denton\u003Cbr \/\u003Edenton at cc dot gatech dot edu\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"466051":{"#nid":"466051","#data":{"type":"event","title":"ARC Colloquium: Martin Farach-Colton - Rutgers University","body":[{"value":"\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC) \u003C\/strong\u003E\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EMartin Farach-Colton - Rutgers University\u003C\/strong\u003E\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EMonday, February 8, 20116\u003C\/strong\u003E\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 West - 1:00 pm\u003C\/strong\u003E\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003E(Refreshments will be served in Klaus 2222 at 2 pm)\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ETitle: \u003Cbr \/\u003E\u003C\/strong\u003EA Field Guide to Write Optimization\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAbstract: \u003Cbr \/\u003E\u003C\/strong\u003EDictionaries are probably the most widely studied and deployed data structures. \u0026nbsp;For large data, write-optimization techniques allow one to insert records much faster than they can be searched. \u0026nbsp;These new techniques are changing the way such dictionaries are used, which leads to new analytical questions. \u0026nbsp;In this talk, I will survey some of the recent work on write-optimized dictionaries and discuss the impact the new algorithmic work is having in the implementation of storage systems.\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EBio: \u003Cbr \/\u003E\u003C\/strong\u003EMartin Farach-Colton\u0026nbsp;received his MD from Johns Hopkins and his PhD in Computer Science from the University of Maryland. \u0026nbsp;He is a Professor Computer Science at Rutgers University. \u0026nbsp;He is CTO and Co-founder of Tokutek, a database company that was founded to commercialize his research. \u0026nbsp;This company was acquired by\u0026nbsp;Percona in 2015. \u0026nbsp;During 2000-2002, he was a Senior Research Scientist at Google. \u0026nbsp;He works on external memory algorithms as well as their\u0026nbsp;application to storage systems.\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Klaus 1116 West at 1 pm"}],"uid":"27466","created_gmt":"2015-11-04 12:01:27","changed_gmt":"2017-04-13 21:17:44","author":"Dani Denton","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2016-02-08T17:00:00-05:00","event_time_end":"2016-02-08T18:00:00-05:00","event_time_end_last":"2016-02-08T18:00:00-05:00","gmt_time_start":"2016-02-08 22:00:00","gmt_time_end":"2016-02-08 23:00:00","gmt_time_end_last":"2016-02-08 23:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"47223","name":"College of Computing"},{"id":"50875","name":"School of Computer Science"},{"id":"70263","name":"ARC"}],"categories":[],"keywords":[{"id":"111051","name":"Algorithm and Randomness Center"},{"id":"4265","name":"ARC"},{"id":"115001","name":"Computational Complexity"},{"id":"114991","name":"Computational Learning Theory"},{"id":"109","name":"Georgia Tech"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78751","name":"Undergraduate students"},{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EDani Denton\u003Cbr \/\u003Edenton at cc dot gatech dot edu\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"486431":{"#nid":"486431","#data":{"type":"event","title":"ARC Colloquium: Ian Munro - University of Waterloo","body":[{"value":"\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC) \u003C\/strong\u003E\u003C\/p\u003E\u003Ch5 align=\u0022center\u0022\u003EIan Munro \u2013 University of Waterloo\u003C\/h5\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EMonday, February 1, 20116\u003C\/strong\u003E\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 West - 1:00 pm\u003C\/strong\u003E\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003E(Refreshments will be served in Klaus 2222 at 2 pm)\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ETitle:\u003Cbr \/\u003E \u003C\/strong\u003EOptimal Search Trees with 2-way Comparisons\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003Cbr \/\u003E \u003C\/strong\u003EThis talk is about finding a polynomial time algorithm that you probably thought was known almost a half century ago, but it wasn\u2019t. The polynomial time algorithm is still rather slow and requires a lot of space to solve, so we also look at extremely good and fast approximate solutions. More specifically \u2026\u003Cbr \/\u003E In 1971, Knuth gave an O(n\u003Csup\u003E2\u003C\/sup\u003E)-time algorithm for the now classic problem of finding an optimal binary search tree. Knuth\u2019s algorithm works only for search trees based on 3-way comparisons, but most modern programming languages and computers support only 2-way comparisons (\u0026lt;, = and \u0026gt;). Until this work, the problem of finding an optimal search tree using 2-way comparisons remained open \u2014 polynomial time algorithms were known only for restricted variants. We solve the general case, giving\u003C\/p\u003E\u003Cp\u003E(i)\u0026nbsp; an O(n\u003Csup\u003E4\u003C\/sup\u003E)-time algorithm and\u003C\/p\u003E\u003Cp\u003E(ii) a linear time algorithm that gives a tree with expected search cost within 2 comparisons of the optimal.\u003C\/p\u003E\u003Cp\u003EThis is joint work with Marek Chrobak, Mordecai Golin, and Neal E. Young.\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Klaus 1116 West at 1 pm"}],"uid":"27466","created_gmt":"2016-01-14 15:10:33","changed_gmt":"2017-04-13 21:17:09","author":"Dani Denton","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2016-02-01T12:00:00-05:00","event_time_end":"2016-02-01T13:00:00-05:00","event_time_end_last":"2016-02-01T13:00:00-05:00","gmt_time_start":"2016-02-01 17:00:00","gmt_time_end":"2016-02-01 18:00:00","gmt_time_end_last":"2016-02-01 18:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"},{"id":"47223","name":"College of Computing"},{"id":"50875","name":"School of Computer Science"}],"categories":[],"keywords":[{"id":"111051","name":"Algorithm and Randomness Center"},{"id":"4265","name":"ARC"},{"id":"115001","name":"Computational Complexity"},{"id":"114991","name":"Computational Learning Theory"},{"id":"109","name":"Georgia Tech"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78751","name":"Undergraduate students"},{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EDani Denton\u003Cbr \/\u003Edenton at cc dot gatech dot edu\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"486491":{"#nid":"486491","#data":{"type":"event","title":"ARC Colloquium: William Gasarch - University of Maryland at College Park","body":[{"value":"\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC) \u003C\/strong\u003E\u003C\/p\u003E\u003Ch2 align=\u0022center\u0022\u003EWilliam Gasarch \u2013 University of Maryland\u003C\/h2\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EWednesday, February 17, 20116\u003C\/strong\u003E\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 East - 1:00 pm\u003C\/strong\u003E\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003E(Refreshments will be served in Klaus 2222 at 2 pm)\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ETitle: \u003Cbr \/\u003E\u003C\/strong\u003EAdvanced Results in the Theory of Languages and Computation which have Simple Proofs\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAbstract: \u003Cbr \/\u003E\u003C\/strong\u003EAutomata theory is about the following: Given a language (a set of strings) how hard is it? Is it regular, context free, or decidable? We give three results that COULD be put in a course on such but are not!\u003C\/p\u003E\u003Col\u003E\u003Cli\u003ERegular, Context free, and Decidable languages are closed under many operations. Note the following: if L is regular (CFL) then SUBSEQ(L) is regular (CFL).\u0026nbsp; This is an easy exercise. But what if L is decidable? Is SUBSEQ(L) decidable? The answer may surprise you!\u003C\/li\u003E\u003Cli\u003EThere are languages L that are regular but the DFA for them is much smaller than the CFG for them. How much smaller? The answer may surprise you!\u003C\/li\u003E\u003Cli\u003EIt is easy to show that COL3 \\le COL4 (three-colorability \\le 4-colorablity). Is COL4 \\le COL3? You probably know that it is by going through the Cook-Levin Theorem. Is there an easier proof? The answer would surprise you if I didn\u0027t ask the question so I\u0027ll just say YES- I will show COL4 \\le COL3 with a simple proof.\u003C\/li\u003E\u003C\/ol\u003E\u003Cp\u003EThe answers may surprise you!\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Klaus 1116 East at 1 pm"}],"uid":"27466","created_gmt":"2016-01-14 15:29:00","changed_gmt":"2017-04-13 21:17:07","author":"Dani Denton","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2016-02-17T12:00:00-05:00","event_time_end":"2016-02-17T13:00:00-05:00","event_time_end_last":"2016-02-17T13:00:00-05:00","gmt_time_start":"2016-02-17 17:00:00","gmt_time_end":"2016-02-17 18:00:00","gmt_time_end_last":"2016-02-17 18:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"},{"id":"47223","name":"College of Computing"},{"id":"50875","name":"School of Computer Science"}],"categories":[],"keywords":[{"id":"111051","name":"Algorithm and Randomness Center"},{"id":"4265","name":"ARC"},{"id":"115001","name":"Computational Complexity"},{"id":"114991","name":"Computational Learning Theory"},{"id":"109","name":"Georgia Tech"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78751","name":"Undergraduate students"},{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EDani Denton\u003Cbr \/\u003Edenton at cc dot gatech dot edu\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"486601":{"#nid":"486601","#data":{"type":"event","title":"ARC Colloquium: John Wilmes - University of Chicago","body":[{"value":"\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC) \u003C\/strong\u003E\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EJohn Wilmes \u2013 University of Chicago\u003C\/strong\u003E\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EMonday, January 25, 20116\u003C\/strong\u003E\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EMiRC 102 A \u0026amp; B - 1:00 pm\u003C\/strong\u003E\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003E(Refreshments will be served in Klaus 2222 at 2 pm)\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ETitle: \u003Cbr \/\u003E\u003C\/strong\u003EThe Isomorphism Problem for Highly Regular Structures\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EThe Graph Isomorphism (GI) problem has been notorious in computational complexity theory for its unresolved complexity status. Until Babai\u0027s recently announced quasipolynomial-time algorithm for GI, the worst-case time-complexity bound of $\\exp(\\tilde{O}(n^{1\/2}))$ where $n$ is the number of vertices (Babai--Luks, 1983), had stood for over 30 years.\u003C\/p\u003E\u003Cp\u003EAmong the obstacles Babai confronts in his recent breakthrough are primitive coherent configurations (PCCs), a class of highly-regular structures generalizing strongly regular graphs. In this talk, we will describe recent progress characterizing the structure and automorphism groups of PCCs and other highly-regular structures, with applications to GI, and we will describe the connections between these results and Babai\u0027s breakthrough.\u003C\/p\u003E\u003Cp\u003EIn particular, in joint work with Sun, we classify the PCCs with the most automorphisms. In joint work with Babai, Chen, Sun, and Teng, we give the first quasipolynomial-time algorithm for strongly regular GI over an entire interval of the exponent of the degree parameter. And in joint work with Babai, we give a $n^{O(\\log n)}$-time algorithm for the important special case of Steiner Design Isomorphism.\u0026nbsp; In all cases, our progress relies on new structural results we prove, especially on new bounds for the rate of expansion of small sets.\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"MIRC 102 A \u0026 B at 1 pm"}],"uid":"27466","created_gmt":"2016-01-14 16:13:25","changed_gmt":"2017-04-13 21:17:07","author":"Dani Denton","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2016-01-25T12:00:00-05:00","event_time_end":"2016-01-25T13:00:00-05:00","event_time_end_last":"2016-01-25T13:00:00-05:00","gmt_time_start":"2016-01-25 17:00:00","gmt_time_end":"2016-01-25 18:00:00","gmt_time_end_last":"2016-01-25 18:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"},{"id":"47223","name":"College of Computing"},{"id":"50875","name":"School of Computer Science"}],"categories":[],"keywords":[{"id":"111051","name":"Algorithm and Randomness Center"},{"id":"4265","name":"ARC"},{"id":"115001","name":"Computational Complexity"},{"id":"114991","name":"Computational Learning Theory"},{"id":"109","name":"Georgia Tech"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78751","name":"Undergraduate students"},{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EDani Denton\u003Cbr \/\u003Edenton at cc dot gatech dot edu\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"492641":{"#nid":"492641","#data":{"type":"event","title":"ARC Colloquium: Antonio Blanca - UC Berkeley","body":[{"value":"\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003ENOTE - Talk is at 2 pm instead of 1 pm.\u003Cbr \/\u003E\u003C\/strong\u003E\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC) \u003C\/strong\u003E\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EAntonio Blanca - UC Berkeley\u003C\/strong\u003E\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EFriday, February 5, 2016\u003C\/strong\u003E\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 East (not West) - 2:00 pm\u003C\/strong\u003E\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003E(Refreshments will be served in Klaus 2222 at 3 pm)\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ETitle: \u003Cbr \/\u003E \u003C\/strong\u003EDynamics for the random-cluster model\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E \u003Cbr \/\u003E The random-cluster model has been widely studied as a unifying framework for random graphs, spin systems and electrical networks, but its dynamics have so far largely resisted analysis. In this talk we present recent results concerning the mixing behavior of natural Markov chains for the random-cluster model in two canonical cases: the mean-field model and the two dimensional lattice graph Z^2. In the mean-field case, we identify a critical regime of the model parameter p in which several natural dynamics undergo an exponential slowdown. In Z^2, we provide tight mixing time bounds for the heat-bath dynamics for all non-critical values of p. These results hold for all values of the second model parameter q \u0026gt; 1.\u003Cbr \/\u003E \u003Cbr \/\u003E Based on joint works with Alistair Sinclair.\u003Cbr \/\u003E \u003Cbr \/\u003E Short Bio: Antonio Blanca is a 5th year PhD student at UC Berkeley advised by Alistair Sinclair. He is interested in algorithms, Markov chain mixing, phase transitions and random structures. He graduated with a BS in Computer Science\/Discrete Math from Georgia Tech.\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Talk is at 2 pm instead of 1 pm - Klaus 1116 West"}],"uid":"27466","created_gmt":"2016-01-29 12:48:17","changed_gmt":"2017-04-13 21:16:51","author":"Dani Denton","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2016-02-05T13:00:00-05:00","event_time_end":"2016-02-05T14:00:00-05:00","event_time_end_last":"2016-02-05T14:00:00-05:00","gmt_time_start":"2016-02-05 18:00:00","gmt_time_end":"2016-02-05 19:00:00","gmt_time_end_last":"2016-02-05 19:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"},{"id":"47223","name":"College of Computing"},{"id":"50875","name":"School of Computer Science"}],"categories":[],"keywords":[{"id":"111051","name":"Algorithm and Randomness Center"},{"id":"4265","name":"ARC"},{"id":"115001","name":"Computational Complexity"},{"id":"114991","name":"Computational Learning Theory"},{"id":"109","name":"Georgia Tech"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78751","name":"Undergraduate students"},{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EDani Denton\u003Cbr \/\u003Edenton at cc dot gatech dot edu\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"493111":{"#nid":"493111","#data":{"type":"event","title":"ARC Theory Day","body":[{"value":"\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC) \u003C\/strong\u003E\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EARC Theory Day\u003Cbr \/\u003E\u003C\/strong\u003E\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EMonday, April 11\u003C\/strong\u003E\u003Cstrong\u003E, 2016\u003C\/strong\u003E\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 - 9:00 am - 4:00 pm\u003Cbr \/\u003E\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EObjective:\u003C\/strong\u003E \u0026nbsp;\u003Cbr \/\u003EAlgorithms and Randomness Center (ARC) Theory Day is an annual event to showcase lectures on exciting new developments in theoretical computer science. This year\u0027s event features four young speakers who are dedicated to investigating some of the most complex questions in theoretical computer science. These guests will discuss a wide range of topics from interior point methods to circuit lower bounds by random projections. The lectures promise to be engaging and discuss techniques to help solve these emerging problems and understand related phenomena.\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EOrganizers:\u003C\/strong\u003E Santosh Vempala, Richard Peng and Dana Randall\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ESchedule:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EMonday, April 11, 2016: \u003Cbr \/\u003E\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E9:30 am \u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; Breakfast\u003Cbr \/\u003E9:50 am \u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; Opening Remarks\u003Cbr \/\u003E10:00 am \u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; \u003Cstrong\u003EVirginia Vassilevska-Williams\u003C\/strong\u003E (Stanford): \u003Cstrong\u003EFine-Grained Algorithms and Complexity\u003Cbr \/\u003E\u003C\/strong\u003E11:00 am \u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; Break\u003Cbr \/\u003E11:15 am\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; \u003Cstrong\u003ERocco Servedio\u003C\/strong\u003E (Columbia): \u003Cstrong\u003ECircuit Lower Bounds via Random Projections\u003Cbr \/\u003E\u003C\/strong\u003E12:15 pm\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; Lunch Break\u003Cbr \/\u003E1:30 pm\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; \u003Cstrong\u003EAaron Sidford \u003C\/strong\u003E(Microsoft Research): \u003Cstrong\u003ERecent Advances in the Theory of Interior Point Methods\u003Cbr \/\u003E\u003C\/strong\u003E2:30 pm \u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; Break\u003Cbr \/\u003E2:45 pm\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; \u003Cstrong\u003ELuca Trevisan\u003C\/strong\u003E (UC Berkeley): \u003Cstrong\u003ERamanujan Graphs\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAbstracts:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EVirginia Vassilevska-Williams (Stanford): \u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E \u003Cbr \/\u003E Fine-Grained Algorithms and Complexity\u003Cbr \/\u003E \u003Cstrong\u003EAbstract:\u003Cbr \/\u003E \u003C\/strong\u003EA central goal of algorithmic research is to determine how fast computational problems can be solved in the worst case. Theorems from complexity theory state that there are problems that, on inputs of size n, can be solved in t(n) time but not in t(n)^{1-eps} time for eps\u0026gt;0. The main challenge is to determine where in this hierarchy various natural and important problems lie. Throughout the years, many ingenious algorithmic techniques have been developed and applied to obtain blazingly fast algorithms for many problems. Nevertheless, for many other central problems, the best known running times are essentially those of the classical algorithms devised for them in the 1950s and 1960s.\u003Cbr \/\u003E \u003Cbr \/\u003E Unconditional lower bounds seem very difficult to obtain, and so practically all known time lower bounds are conditional. For years, the main tool for proving hardness of computational problems have been NP-hardness reductions, basing hardness on P\\neq NP. However, when we care about the exact running time (as opposed to merely polynomial vs non-polynomial), NP-hardness is not applicable, especially if the running time is already polynomial. In recent years, a new theory has been developed, based on \u201cfine-grained reductions\u201d that focus on exact running times. The goal of these reductions is as follows. Suppose problem A is solvable in a(n) time and problem B in b(n) time, and no a(n)^{1-eps} and b(n)^{1-eps} algorithms are known for A and B respectively. Then, if A is fine-grained reducible to problem B (for a(n) and b(n)), a b(n)^{1-eps} time algorithm for B (for any eps\u0026gt;0) implies an a(n)^{1-eps\u0027} algorithm for A (for some eps\u0027\u0026gt;0). Now, mimicking NP-hardness, the approach is to (1) select a key problem X that is conjectured to require t(n)^{1-o(1)} time for some t, and (2) reduce X in a fine-grained way to many important problems. This approach has led to the discovery of many meaningful relationships between problems, and even sometimes to equivalence classes.\u003Cbr \/\u003E \u003Cbr \/\u003E In this talk I will give an overview or the current progress in this area of study, and will highlight some new exciting developments.\u003Cbr \/\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E\u003Cbr \/\u003E Virginia V. Williams is an assistant professor of computer science at Stanford University. She obtained her Ph.D. in 2008 from Carnegie Mellon where she was advised by Guy Blelloch. Before joining Stanford, she spent time at the Institute for Advanced Study and UC Berkeley. Her main area of interest is broadly in computational complexity, the design and analysis of algorithms, and more specifically in graph and matrix algorithms.\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ERocco Servedio (Columbia University)\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E \u0026nbsp;\u003Cbr \/\u003E Circuit Lower Bounds via Random Projections\u003Cbr \/\u003E \u003Cstrong\u003EAbstract:\u003C\/strong\u003E \u003Cbr \/\u003E Random restrictions are a classical and\u0026nbsp;important technique for proving circuit lower bounds.\u0026nbsp; This talk will discuss\u0026nbsp;\u003Cem\u003Erandom\u0026nbsp;projections,\u0026nbsp;\u003C\/em\u003Ea generalization of random restrictions.\u0026nbsp; While conceptually simple, random projections have led to recent advances on several well-studied lower bound problems involving small-depth circuits.\u0026nbsp; We will see how random projections play a key role in the following results:\u003C\/p\u003E\u003Cul\u003E\u003Cli\u003EAn average-case depth hierarchy theorem for Boolean circuits.\u0026nbsp;This gives an average-case extension of the classical (worst-case) depth hierarchy theorem of\u0026nbsp;Sipser, Yao, and\u0026nbsp;Hastad, and resolves a main open problem in\u0026nbsp;Hastad\u2019s\u0026nbsp;1986 PhD thesis.\u0026nbsp; Via a classical connection between Boolean circuits and structural complexity, this hierarchy theorem implies that the polynomial hierarchy is infinite relative to a random oracle with probability 1, resolving a longstanding conjecture of\u0026nbsp;Hastad,\u0026nbsp;Cai\u0026nbsp;and\u0026nbsp;Babai\u0026nbsp;from the 1980s.\u0026nbsp; (Joint work with Ben\u0026nbsp;Rossman\u0026nbsp;and Li-Yang Tan.)\u003C\/li\u003E\u003Cli\u003EThe first super-polynomial lower bounds against the \u201cdepth d\u0026nbsp;Frege\u201d proof system for some polylogarithmic depth d.\u0026nbsp; Previous super-polynomial lower bounds (Pitassi\u0026nbsp;et al. 1993,\u0026nbsp;Krajicek\u0026nbsp;et al. 1995) were only known against depth-d\u0026nbsp;Frege\u0026nbsp;for d=Theta(log log n).\u0026nbsp; (Joint work with Toni\u0026nbsp;Pitassi, Ben\u0026nbsp;Rossman, and Li-Yang Tan.)\u003C\/li\u003E\u003Cli\u003EA nearly optimal size lower bound on small-depth circuits that determine whether a graph has a short s-to-t path.\u0026nbsp; We show that depth-d circuits for distance-k connectivity on n-node graphs must have size n^{\\Omega(k^{1\/d}\/d)}; the previous best size lower bounds for this problem were n^{k^{\\exp(-O(d))}} (due to\u0026nbsp;Beame\u0026nbsp;et al. 1998) and n^{\\Omega((\\log k)\/d)} (due to\u0026nbsp;Rossman\u0026nbsp;2014).\u0026nbsp; (Joint work with Xi Chen, Igor Oliveira and Li-Yang Tan.)\u003C\/li\u003E\u003C\/ul\u003E\u003Cp\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E \u0026nbsp;\u003Cbr \/\u003E Rocco Servedio is an Associate Professor of Computer Science at Columbia University. His research interests center around computational learning theory, property testing, and computational complexity.\u0026nbsp; Rocco is the recipient of an NSF Career Award and a Sloan Foundation Fellowship; his research has received Best Paper \/ Best Student Paper awards from the CCC, COLT, FOCS, and STOC conferences.\u0026nbsp; His teaching at Columbia has been recognized with the Department of Computer Science Distinguished Teaching Award, the Columbia Engineering Alumni Association Distinguished Faculty Teaching Award, and the Columbia Presidential Teaching Award.\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003E\u003Cbr \/\u003E\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAaron Sidford (Microsoft Research)\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ETitle\u003C\/strong\u003E: \u003Cbr \/\u003E Recent Advances in the Theory of Interior Point Methods\u0026nbsp;\u003Cbr \/\u003E \u003Cstrong\u003EAbstract\u003C\/strong\u003E:\u0026nbsp;\u003Cbr \/\u003E In this talk I will survey recent results on\u0026nbsp;using interior point techniques\u0026nbsp;to design provably efficient algorithms. I will give a brief overview of this powerful convex optimization technique and discuss how it has been used to improve the running time of fundamental optimization problems such as maximum flow, linear programming, and most recently the geometric median problem. In particular, I will highlight recent joint work with Michael Cohen, Yin Tat Lee, Jakub Pachocki, and Gary Miller building on these techniques to obtain the first nearly linear time algorithm for computing the geometric median. No previous experience with interior point methods required.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EBio\u003C\/strong\u003E:\u0026nbsp;\u003Cbr \/\u003E Aaron Sidford is a postdoctoral researcher at Microsoft Research New England and will be joining the department of Management Science and Engineering at Stanford University in Fall 2016. Aaron received his PhD from the EECS department at MIT where he was advised by Professor Jonathan Kelner.\u0026nbsp;\u003Cbr \/\u003E \u003Cbr \/\u003EAaron\u2019s research interests lie broadly in the theory of computation and the design and analysis of algorithms. He is particularly interested in work at the intersection of continuous optimization, graph theory, numerical linear algebra, and data structures.\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003E\u003Cbr \/\u003E\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ELuca Trevisan (UC Berkeley)\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E \u003Cbr \/\u003E Ramanujan Graphs\u003Cbr \/\u003E \u003Cstrong\u003EAbstract:\u003C\/strong\u003E \u003Cbr \/\u003E We will review what is known about existence and constructions of Ramanujan graphs, which are the best possible expander graphs from the point of view of spectral expansion.\u003Cbr \/\u003E We will talk about Friedman\u0027s result that random graphs are nearly Ramanujan, and recent simplifications of his proof, about a characterization of Ramanujan graphs in terms of the Ihara zeta function, about number-theoretic efficient constructions, and about the recent non-constructive existence results of Marcus, Spielman, and Srivastava.\u003Cbr \/\u003E \u003Cstrong\u003EBio:\u003C\/strong\u003E\u003Cbr \/\u003E Luca Trevisan is a professor of Electrical Engineering and Computer Sciences and of Mathematics at U.C. Berkeley, and a senior scientist at the Simons Institute for the Theory of Computing. In the past, he has also taught at Columbia University and at Stanford. He is interested in several aspects of computational complexity theory and, in the last few years, he has been working on spectral graph theory.\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Klaus 1116 East \u0026 West - Invited Speakers: Rocco Servedio (Columbia), Aaron Sidford (Microsoft Research), Luca Trevisan (UC Berkeley) and Virginia Vassilevska-Williams (Stanford)"}],"uid":"27466","created_gmt":"2016-01-31 16:15:32","changed_gmt":"2017-04-13 21:16:50","author":"Dani Denton","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2016-04-11T10:30:00-04:00","event_time_end":"2016-04-11T17:00:00-04:00","event_time_end_last":"2016-04-11T17:00:00-04:00","gmt_time_start":"2016-04-11 14:30:00","gmt_time_end":"2016-04-11 21:00:00","gmt_time_end_last":"2016-04-11 21:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"},{"id":"47223","name":"College of Computing"},{"id":"50875","name":"School of Computer Science"}],"categories":[],"keywords":[{"id":"111051","name":"Algorithm and Randomness Center"},{"id":"4265","name":"ARC"},{"id":"115001","name":"Computational Complexity"},{"id":"114991","name":"Computational Learning Theory"},{"id":"109","name":"Georgia Tech"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78751","name":"Undergraduate students"},{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EDani Denton\u003Cbr \/\u003Edenton at cc dot gatech dot edu\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"500221":{"#nid":"500221","#data":{"type":"event","title":"ARC Colloquium: Marco-Dick Yun Kuen Cheung - University of Vienna","body":[{"value":"\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC) \u003C\/strong\u003E\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EMarco-Dick Yun Kuen Cheung \u0026nbsp;- University of Vienna\u003Cbr \/\u003E\u003C\/strong\u003E\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EMonday, February 29, 20116\u003C\/strong\u003E\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 West - 1:00 pm\u003C\/strong\u003E\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003E(Refreshments will be served in Klaus 2222 at 2 pm)\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ETitle: \u003Cbr \/\u003E \u003C\/strong\u003EGraph Minors for Preserving Terminal Distances Approximately\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAbstract: \u003Cbr \/\u003E \u003C\/strong\u003EGiven a graph where vertices are partitioned into k terminals and non-terminals, the goal is to compress the graph (i.e., reduce the number of non-terminals) using minor operations while preserving terminal distances approximately. The distortion of a compressed graph is the maximum multiplicative blow-up of distances between all pairs of terminals. We study the trade-off between the number of non-terminals and the distortion.\u0026nbsp; This problem generalizes the Steiner Point Removal (SPR) problem, in which all non-terminals must be removed.\u003Cbr \/\u003E \u003Cbr \/\u003E We introduce a novel black-box reduction to convert any lower bound on distortion for the SPR problem into a super-linear lower bound on the number of non-terminals, with the same distortion, for our problem. This allows us to show that there exist graphs such that every minor with distortion less than 2 \/ 2.5\/ 3\u0026nbsp; must have \\Omega(k^2) \/ \\Omega(k^{5\/4}) \/ \\Omega(k^{6\/5}) non-terminals, plus more trade-offs in between. The black-box reduction has an interesting consequence: if the tight lower bound on distortion for the SPR problem is super-constant, then allowing any linear (in k) non-terminals will \u003Cem\u003Enot\u003C\/em\u003E help improving the lower bound to a constant.\u003Cbr \/\u003E \u003Cbr \/\u003E We also build on the existing results on spanners, distance oracles and connected 0-extensions to show a number of upper bounds for general graphs, planar graphs, graphs that exclude a fixed minor and bounded treewidth graphs. Among others, we show that any graph admits a minor with O(log k) distortion and O(k^2) non-terminals, and any planar graph admits a minor with $1+epsilon$ distortion and O(k^2 log^2 k \/ epsilon^2) non-terminals.\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Klaus 1116 West at 1 pm"}],"uid":"27466","created_gmt":"2016-02-15 10:03:04","changed_gmt":"2017-04-13 21:16:39","author":"Dani Denton","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2016-02-29T12:00:00-05:00","event_time_end":"2016-02-29T13:00:00-05:00","event_time_end_last":"2016-02-29T13:00:00-05:00","gmt_time_start":"2016-02-29 17:00:00","gmt_time_end":"2016-02-29 18:00:00","gmt_time_end_last":"2016-02-29 18:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"},{"id":"47223","name":"College of Computing"},{"id":"50875","name":"School of Computer Science"}],"categories":[],"keywords":[{"id":"111051","name":"Algorithm and Randomness Center"},{"id":"4265","name":"ARC"},{"id":"115001","name":"Computational Complexity"},{"id":"114991","name":"Computational Learning Theory"},{"id":"109","name":"Georgia Tech"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78751","name":"Undergraduate students"},{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EDani Denton\u003Cbr \/\u003Edenton at cc dot gatech dot edu\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"500231":{"#nid":"500231","#data":{"type":"event","title":"ARC Colloquium: Alon Orlitsky - University of CA, San Diego","body":[{"value":"\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC) \u003C\/strong\u003E\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EAlon Orlitsky - University of CA, San Diego\u003C\/strong\u003E\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EMonday, April 18, 20116\u003C\/strong\u003E\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 West - 1:00 pm\u003C\/strong\u003E\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003E(Refreshments will be served in Klaus 2222 at 2 pm)\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp;\u003Cbr \/\u003E\u003C\/strong\u003ELearning and Forecasting over Large Domains: The Art of the Doable\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003Cbr \/\u003E \u003C\/strong\u003ELearning a distribution and forecasting its outcomes are important tasks whose complexity increases with the distribution\u0027s support size. We consider useful and natural formulations of these two tasks that allow them to be performed with a sample whose size is fixed and independent of the distribution or its support size.\u003Cbr \/\u003E \u003Cbr \/\u003E Learning a distribution to a given KL divergence requires a sample size that increases linearly with the support size. We show that with n samples, the distribution can be learned to a KL divergence that is at most 1\/sqrt(n) higher than that achievable by any estimator, even one that knows the distribution up to permutation.\u003Cbr \/\u003E \u003Cbr \/\u003E Estimating a distribution\u0027s support size may require an unbounded number samples. Yet we show that with n samples, we can estimate the number of hitherto unseen elements that will be observed in up to n*log(n) new samples, thereby estimating the effective support of a much larger sample.\u0026nbsp;\u003Cbr \/\u003E \u003Cbr \/\u003E Joint work with Ananda Theertha Suresh and Yihong Wu.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E\u003Cbr \/\u003E Alon Orlitsky received B.Sc. degrees in Mathematics and Electrical Engineering from Ben Gurion University in 1980 and 1981, and M.Sc. and Ph.D. degrees in Electrical Engineering from Stanford University in 1982 and 1986.\u003Cbr \/\u003E \u003Cbr \/\u003E From 1986 to 1996 he was with the Communications Analysis Research Department of Bell Laboratories. He spent the following year as a quantitative analyst at D.E. Shaw and Company, an investment firm in New York City. In 1997 he joined the University of California San Diego, where he is currently a professor of Electrical and Computer Engineering and of Computer Science and Engineering.\u0026nbsp; His research concerns information theory, statistical modeling, and machine learning.\u003Cbr \/\u003E \u003Cbr \/\u003E From 2011 to 2014 Alon directed UCSD\u0027s Center for Wireless Communications, and since 2006 he has directed the Information Theory and Applications Center. He is currently the president of the Information Theory Society. He has co-organized numerous programs on information theory, machine learning, and statistics, including the Information Theory and Applications Workshop that he started in 2006 and has helped organize since.\u003Cbr \/\u003E \u003Cbr \/\u003E Alon is a recipient of the 1981 ITT International Fellowship and the 1992 IEEE W.R.G. Baker Paper Award, and co-recipient of the 2006 Information Theory Society Paper Award and the 2016 NIPS Paper Award. He is a fellow of the IEEE, and holds the Qualcomm Chair for Information Theory and its Applications at UCSD.\u003Cbr \/\u003E \u003Cbr \/\u003E \u003Cstrong\u003EURL:\u003C\/strong\u003E \u003Ca href=\u0022http:\/\/alon.ucsd.edu\/\u0022\u003Ehttp:\/\/alon.ucsd.edu\/\u003C\/a\u003E\u003Cbr \/\u003E \u003Cbr \/\u003E \u003Cstrong\u003EHost:\u003C\/strong\u003E Vijay Vazirani (\u003Ca href=\u0022mailto:vazirani@cc.gatech.edu\u0022\u003Evazirani@cc.gatech.edu\u003C\/a\u003E)\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Klaus 1116 West at 1 pm"}],"uid":"27466","created_gmt":"2016-02-15 10:09:58","changed_gmt":"2017-04-13 21:16:39","author":"Dani Denton","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2016-04-18T14:00:00-04:00","event_time_end":"2016-04-18T15:00:00-04:00","event_time_end_last":"2016-04-18T15:00:00-04:00","gmt_time_start":"2016-04-18 18:00:00","gmt_time_end":"2016-04-18 19:00:00","gmt_time_end_last":"2016-04-18 19:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"},{"id":"47223","name":"College of Computing"},{"id":"50875","name":"School of Computer Science"}],"categories":[],"keywords":[{"id":"111051","name":"Algorithm and Randomness Center"},{"id":"4265","name":"ARC"},{"id":"115001","name":"Computational Complexity"},{"id":"114991","name":"Computational Learning Theory"},{"id":"109","name":"Georgia Tech"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78751","name":"Undergraduate students"},{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EDani Denton\u003Cbr \/\u003Edenton at cc dot gatech dot edu\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"503471":{"#nid":"503471","#data":{"type":"event","title":"ARC Colloquium: Ilya Safro - Clemson University","body":[{"value":"\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC) \u003C\/strong\u003E\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EIlya Safro - Clemson University\u003C\/strong\u003E\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EMonday, March 7, 20116\u003Cbr \/\u003EKlaus 1116 West - 1:00 pm\u003Cbr \/\u003E(Refreshments will be served in Klaus 2222 at 2 pm)\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ETitle: \u003Cbr \/\u003E\u003C\/strong\u003EMultiscale Methods for Discrete Optimization on Graphs\u003Cbr \/\u003E\u003Cstrong\u003EAbstract: \u003Cbr \/\u003E\u003C\/strong\u003EIn many real-world problems, a big scale gap can be observed between micro- and macroscopic scales of the problem because of the difference in mathematical (engineering, social, biological, physical, etc.) models and\/or laws at different scales. The main objective of multigrid-inspired multiscale algorithms is to create a hierarchy of problems, each representing the original problem at different coarse scales with fewer degrees of freedom. We will discuss different strategies of creating these hierarchies for discrete optimization problems on large-scale graphs. These strategies are inspired by the classical multigrid frameworks such as geometric multigrid, algebraic multigrid and full approximation scheme. We will present in details a multiscale framework for linear arrangement, network compression, k-partitioning and clustering, network generation, sparsification, and epidemics response problems. Time permits, a multigrid-inspired algorithm for the support vector machines will be presented.\u003C\/p\u003E\u003Cp\u003EUrl: \u003Ca href=\u0022http:\/\/people.cs.clemson.edu\/~isafro\/\u0022\u003Ehttp:\/\/people.cs.clemson.edu\/~isafro\/\u003C\/a\u003E\u003C\/p\u003E\u003Cp\u003EHost: Richard Peng (\u003Ca href=\u0022mailto:rpeng@cc.gatech.edu\u0022\u003Erpeng@cc.gatech.edu\u003C\/a\u003E)\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Klaus 1116 West at 1 pm"}],"uid":"27466","created_gmt":"2016-02-19 10:55:09","changed_gmt":"2017-04-13 21:16:35","author":"Dani Denton","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2016-03-07T12:00:00-05:00","event_time_end":"2016-03-07T13:00:00-05:00","event_time_end_last":"2016-03-07T13:00:00-05:00","gmt_time_start":"2016-03-07 17:00:00","gmt_time_end":"2016-03-07 18:00:00","gmt_time_end_last":"2016-03-07 18:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"},{"id":"47223","name":"College of Computing"},{"id":"50875","name":"School of Computer Science"}],"categories":[],"keywords":[{"id":"111051","name":"Algorithm and Randomness Center"},{"id":"4265","name":"ARC"},{"id":"115001","name":"Computational Complexity"},{"id":"114991","name":"Computational Learning Theory"},{"id":"109","name":"Georgia Tech"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78751","name":"Undergraduate students"},{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EDani Denton\u003Cbr \/\u003Edenton at cc dot gatech dot edu\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"517551":{"#nid":"517551","#data":{"type":"event","title":"ARC Colloquium: Amit Sahai - UCLA","body":[{"value":"\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC) \u003C\/strong\u003E\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EAmit Sahai\u003Cbr \/\u003E\u003C\/strong\u003E\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EFriday, April 15, 20116\u003C\/strong\u003E\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 West - 2:00 pm\u003C\/strong\u003E\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003E(Refreshments will be served in Klaus Atrium at 3 pm)\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ETitle: \u003Cbr \/\u003E\u003C\/strong\u003EHiding Secrets in Software\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003Cbr \/\u003EThe goal of general-purpose program obfuscation is to make an arbitrary computer program \u201cunintelligible\u201d while preserving its functionality. Obfuscation allows us to achieve a powerful capability: software that can keep a secret. This talk will cover recent advances in obfuscation research, yielding constructions of general-purpose obfuscation mechanisms based on new mathematical structures.\u003Cstrong\u003E\u003Cbr \/\u003EBio: \u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EProfessor Amit Sahai received his Ph.D. in Computer Science from MIT in 2000. From 2000 to 2004, he was on the faculty at Princeton University; in 2004 he joined UCLA, where he currently holds the position of Professor of Computer Science. His research interests are in security and cryptography, and theoretical computer science more broadly. He is the co-inventor of Attribute-Based Encryption, Functional Encryption, and Indistinguishability Obfuscation. He has published more than 100 original technical research papers at venues such as the ACM Symposium on Theory of Computing (STOC), CRYPTO, and the Journal of the ACM. He has given a number of invited talks at institutions such as MIT, Stanford, and Berkeley, including the 2004 Distinguished Cryptographer Lecture Series at NTT Labs, Japan. Professor Sahai is the recipient of numerous honors; he was named an Alfred P. Sloan Foundation Research Fellow in 2002, received an Okawa Research Grant Award in 2007, a Xerox Foundation Faculty Award in 2010, a Google Faculty Research Award in 2010, and a 2012 Pazy Memorial Award. He was awarded the 2016 Lockheed Martin Excellence in Teaching Award. His research has been covered by several news agencies including the BBC World Service, Quanta Magazine, Wired, and IEEE Spectrum.\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EUrl:\u003C\/strong\u003E \u003Ca href=\u0022http:\/\/web.cs.ucla.edu\/~sahai\/\u0022 title=\u0022http:\/\/web.cs.ucla.edu\/~sahai\/\u0022\u003Ehttp:\/\/web.cs.ucla.edu\/~sahai\/\u003C\/a\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EHost:\u003C\/strong\u003E Lance Fortnow (\u003Ca href=\u0022mailto:fortnow@cc.gatech.edu\u0022\u003Efortnow@cc.gatech.edu\u003C\/a\u003E)\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Talk is at 2 pm instead of 1 pm - Klaus 1116 West"}],"uid":"27466","created_gmt":"2016-03-25 11:18:57","changed_gmt":"2017-04-13 21:16:11","author":"Dani Denton","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2016-04-15T15:00:00-04:00","event_time_end":"2016-04-15T16:00:00-04:00","event_time_end_last":"2016-04-15T16:00:00-04:00","gmt_time_start":"2016-04-15 19:00:00","gmt_time_end":"2016-04-15 20:00:00","gmt_time_end_last":"2016-04-15 20:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"},{"id":"47223","name":"College of Computing"},{"id":"50875","name":"School of Computer Science"}],"categories":[],"keywords":[{"id":"111051","name":"Algorithm and Randomness Center"},{"id":"4265","name":"ARC"},{"id":"115001","name":"Computational Complexity"},{"id":"114991","name":"Computational Learning Theory"},{"id":"109","name":"Georgia Tech"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78751","name":"Undergraduate students"},{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EDani Denton\u003Cbr \/\u003Edenton at cc dot gatech dot edu\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"542021":{"#nid":"542021","#data":{"type":"event","title":"ARC Talk: David Woodruff - IBM","body":[{"value":"\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EDavid Woodruff - IBM\u003Cbr \/\u003E\u003C\/strong\u003E\u003Cstrong\u003ETuesday, June 7, 2016\u003Cbr \/\u003E\u003C\/strong\u003E\u003Cstrong\u003EKlaus Conference Room 2100 - 2:00 pm\u003C\/strong\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ETitle:\u003Cbr \/\u003E\u003C\/strong\u003EAn Optimal Algorithm for Finding L2 Heavy Hitters\u003Cbr \/\u003E\u003Cbr \/\u003E\u003Cstrong\u003EAbstract:\u003Cbr \/\u003E\u003C\/strong\u003EWe consider the problem of finding the most frequent items in a stream of items from a universe of size n. Namely, we consider returning all l_2-heavy hitters, i.e., those items j for which f_j \u0026gt;= eps sqrt{F_2}, where f_j is the number of occurrences of item j, and F_2 = sum_i f_i^2 is the second moment of the stream. In 2002, Charikar, Chen, and Farach-Colton suggested the CountSketch data structure, which solves this using log^2 n bits of space (for constant eps). The only known lower bound is log n bits. Using Gaussian processes, we show it is possible to achieve an optimal log n bits of space. Our technique resolves a number of other questions in data streams.\u003C\/p\u003E\u003Cp\u003EBased on work with Vladimir Braverman, Stephen Chestnut, and Nikita Ivkin (STOC \u002716) and work with Vladimir Braverman, Stephen Chestnut, Nikita Ivkin, Jelani Nelson, and Zhengyu Wang.\u003Cbr \/\u003E\u003Cbr \/\u003EHost: Santosh Vempala\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Klaus 2100 at 2 pm"}],"uid":"27466","created_gmt":"2016-06-06 09:20:02","changed_gmt":"2017-04-13 21:15:40","author":"Dani Denton","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2016-06-07T15:00:00-04:00","event_time_end":"2016-06-07T16:00:00-04:00","event_time_end_last":"2016-06-07T16:00:00-04:00","gmt_time_start":"2016-06-07 19:00:00","gmt_time_end":"2016-06-07 20:00:00","gmt_time_end_last":"2016-06-07 20:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[{"id":"111051","name":"Algorithm and Randomness Center"},{"id":"4265","name":"ARC"},{"id":"115001","name":"Computational Complexity"},{"id":"114991","name":"Computational Learning Theory"},{"id":"109","name":"Georgia Tech"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78751","name":"Undergraduate students"},{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003Edenton at cc dot gatech dot edu\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"550161":{"#nid":"550161","#data":{"type":"event","title":"ARC Colloquium:  Shayan Oveis Gharan (Washington)","body":[{"value":"\u003Cp style=\u0022color:maroon;\u0022\u003EVideo of this talk is available at: \u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/55876\u0022\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/55876\u003C\/a\u003E\u003C\/p\u003E\r\nFull collection of talk videos are available at:  \r\n\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/a\u003E\r\n\r\n\u003Cbr\u003E\r\n\u003Cbr\u003E\r\n\r\n\r\n\u003Cp  align=\u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp  align=\u0022center\u0022\u003E\u003Ca href=\u0022http:\/\/homes.cs.washington.edu\/~shayan\/\u0022\u003E\u003Cstrong\u003EShayan Oveis Gharan \u0026ndash; \u003C\/strong\u003E\u003Cstrong\u003EUniversity of Washington\u003C\/strong\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp  align=\u0022center\u0022\u003E\u003Cstrong\u003EMonday, September 12, 2016\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp  align=\u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 East - 11am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle: \u0026nbsp;\u003C\/strong\u003E\u003Cem\u003EStrongly Rayleigh distributions and their Applications in Algorithm Design\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract\u003C\/strong\u003E:\u003C\/p\u003E\r\n\r\n\u003Cp\u003EA multivariate polynomial p(z1,...,zn) is stable if p(z1,...,zn) \u0026lt;\u0026gt; 0 whenever Im(zi)\u0026gt;0 for all i. Strongly Rayleigh distributions are probability distributions on 0-1 random variables whose generating polynomial is stable. They can be seen as a natural generalization of product distributions.\u0026nbsp;Borcea, Branden and Liggett used\u0026nbsp;the geometry of stable polynomials to prove numerous properties of strongly Rayleigh distributions,\u0026nbsp;including negative association, and closure under conditioning and truncation.\u003Cbr \/\u003E\r\nIn this talk I will go over basic properties of these distributions, and then I will describe several algorithmic applications.\u003Cbr \/\u003E\r\nBased on joint works with Nima Anari, Alireza Rezaei,\u0026nbsp;Mohit Singh, Amin Saberi.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EShayan Oveis Gharan is an assistant professor in the \u003Ca href=\u0022https:\/\/www.cs.washington.edu\u0022\u003Ecomputer science and engineering\u003C\/a\u003E department at \u003Ca href=\u0022http:\/\/uw.edu\u0022\u003EUniversity of Washington\u003C\/a\u003E.\u0026nbsp; He received his PhD from the \u003Ca href=\u0022http:\/\/msande.stanford.edu\u0022\u003EMS\u0026amp;E department\u003C\/a\u003E at \u003Ca href=\u0022http:\/\/stanford.edu\u0022\u003EStanford University\u003C\/a\u003E in 2013 advised by \u003Ca href=\u0022http:\/\/stanford.edu\/%7Esaberi%22\u0022\u003EAmin Saberi\u003C\/a\u003E and \u003Ca href=\u0022http:\/\/www.eecs.berkeley.edu\/%7Eluca\/\u0022\u003ELuca Trevisan\u003C\/a\u003E.\u0026nbsp; Before joining \u003Ca href=\u0022http:\/\/www.washington.edu\/\u0022\u003EUW\u003C\/a\u003E he spent one and a half years as a postdoctoral \u003Ca href=\u0022http:\/\/millerinstitute.berkeley.edu\u0022\u003EMiller Fellow\u003C\/a\u003E at \u003Ca href=\u0022http:\/\/www.berkeley.edu\/\u0022\u003EUC Berkeley\u003C\/a\u003E where his host was \u003Ca href=\u0022http:\/\/www.cs.berkeley.edu\/%7Evazirani\/\u0022\u003EUmesh Vazirani\u003C\/a\u003E. He did his undergraduate studies at the \u003Ca href=\u0022http:\/\/ce.sharif.edu\u0022\u003EComputer Engineering department\u003C\/a\u003E at \u003Ca href=\u0022http:\/\/sharif.edu\u0022\u003ESharif University\u003C\/a\u003E.\u003Cbr \/\u003E\r\nShayan\u0026#39;s research includes Algorithm design, Graph Theory and Applied Probability.\u0026nbsp; He received ACM doctoral dissertation award honorable mention for his PhD thesis \u0026quot;New Rounding Techniques for the Design and Analysis of Approximation Algorithms\u0026quot; in 2013. He and his coauthors received best paper awards at SODA 2010 and FOCS 2011 for their works on the Traveling Salesman Problem.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EURL: \u003Ca href=\u0022http:\/\/homes.cs.washington.edu\/~shayan\/\u0022\u003Ehttp:\/\/homes.cs.washington.edu\/~shayan\/\u003C\/a\u003E\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Strongly Rayleigh distributions and their Applications in Algorithm Design (Klaus 1116 E at 11am)"}],"uid":"27466","created_gmt":"2016-07-01 15:50:54","changed_gmt":"2017-04-13 21:15:26","author":"Dani Denton","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2016-09-12T12:00:00-04:00","event_time_end":"2016-09-12T13:00:00-04:00","event_time_end_last":"2016-09-12T13:00:00-04:00","gmt_time_start":"2016-09-12 16:00:00","gmt_time_end":"2016-09-12 17:00:00","gmt_time_end_last":"2016-09-12 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"related_links":[{"url":"http:\/\/homes.cs.washington.edu\/~shayan\/","title":"Shayan Oveis Gharan"}],"groups":[{"id":"70263","name":"ARC"},{"id":"50875","name":"School of Computer Science"}],"categories":[],"keywords":[{"id":"92341","name":"Algorithms and Randomness Center"},{"id":"4265","name":"ARC"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"78751","name":"Undergraduate students"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EDani Denton\u003C\/p\u003E\r\n\r\n\u003Cp\u003Edenton at cc dot gatech dot edu\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"553001":{"#nid":"553001","#data":{"type":"event","title":"ARC Colloquium: Brendan Lucier (Microsoft Research)","body":[{"value":"\u003Cp style=\u0022color:maroon;\u0022\u003EVideo of this talk is available at: \u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/55928\u0022\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/55928\u003C\/a\u003E\u003C\/p\u003E\r\nFull collection of talk videos are available at:  \r\n\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/a\u003E\r\n\r\n\u003Cbr\u003E\r\n\u003Cbr\u003E\r\n\r\n\r\n\r\n\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003E\u003Ca href=\u0022http:\/\/research.microsoft.com\/en-us\/um\/people\/brlucier\/\u0022\u003EBrendan Lucier\u003C\/a\u003E \u0026ndash; Microsoft Research\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EMonday, October 3, 2016\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 East - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u003Cbr \/\u003E\r\nPrices, Auctions, and Combinatorial Prophet Inequalities\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003E\u003Cbr \/\u003E\r\nThe most common way to sell resources, from apples to business licenses to concert tickets, is to post prices. A choice of prices can be viewed as an algorithm for an online stochastic optimization problem, which makes decisions using value thresholds. This connection provides an opportunity to use the famous prophet inequality -- which describes the power of threshold rules -- to study pricing problems, and vice-versa. In this talk I\u0026#39;ll present a general framework for deriving new prophet inequalities using economic insights from pricing, with algorithmic applications. Along the way, I\u0026#39;ll describe an unexpected connection between posted prices and equilibria of non-truthful auctions.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EBased on joint works with Paul Duetting, Michal Feldman, Nick Gravin, and Thomas Kesselheim.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EBio: \u003C\/strong\u003E\u003Cbr \/\u003E\r\nBrendan Lucier is a Researcher at Microsoft Research, New England. Prior to joining Microsoft, he received his Ph.D. in Computer Science from the University of Toronto. His research interests lie in the intersection of theoretical Computer Science and Economics, and include algorithmic market design, algorithmic pricing, and social processes on networks. He is especially interested in the tradeoffs between simplicity, robustness, and optimality in markets for complex goods and services.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022http:\/\/research.microsoft.com\/en-us\/um\/people\/brlucier\/\u0022\u003ESpeaker\u0026#39;s webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022http:\/\/www.arc.gatech.edu\/hg\/item\/553001\u0022\u003ESeminar webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022http:\/\/arc.gatech.edu\/node\/114\u0022\u003EFall 2016 ARC Seminar Schedule\u003C\/a\u003E\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Prices, Auctions, and Combinatorial Prophet Inequalities (Klaus 1116 E at 11am)"}],"uid":"27466","created_gmt":"2016-07-15 07:55:08","changed_gmt":"2017-04-13 21:15:23","author":"Dani Denton","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2016-10-03T12:00:00-04:00","event_time_end":"2016-10-03T13:00:00-04:00","event_time_end_last":"2016-10-03T13:00:00-04:00","gmt_time_start":"2016-10-03 16:00:00","gmt_time_end":"2016-10-03 17:00:00","gmt_time_end_last":"2016-10-03 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"},{"id":"47223","name":"College of Computing"},{"id":"50875","name":"School of Computer Science"}],"categories":[],"keywords":[{"id":"111051","name":"Algorithm and Randomness Center"},{"id":"4265","name":"ARC"},{"id":"115001","name":"Computational Complexity"},{"id":"114991","name":"Computational Learning Theory"},{"id":"109","name":"Georgia Tech"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"78751","name":"Undergraduate students"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"Dani Denton \r\n","format":"plain_text"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"560051":{"#nid":"560051","#data":{"type":"event","title":"ARC Colloquium: David Karger (MIT)","body":[{"value":"\u003Cp style=\u0022color:maroon;\u0022\u003EVideo of this talk is available at: \u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/55915\u0022\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/55915\u003C\/a\u003E\u003C\/p\u003E\r\nFull collection of talk videos are available at:  \r\n\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/a\u003E\r\n\r\n\u003Cbr\u003E\r\n\u003Cbr\u003E\r\n\r\n\r\n\u003Cp  align=\u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align=\u0022center\u0022\u003E\u003Ca href=\u0022http:\/\/people.csail.mit.edu\/karger\/\u0022\u003E\u003Cstrong\u003EDavid Karger - MIT\u003C\/strong\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EMonday, September 26, 2016\u003Cbr \/\u003E\r\nKlaus 1116 East - 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u003Cbr \/\u003E\r\nA Fast and Simple Unbiased Estimator for Network (Un)reliability\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract\u003C\/strong\u003E:\u003Cbr \/\u003E\r\nThe following procedure yields an unbiased estimator for the disconnection probability of an n-vertex graph with minimum cut c if every edge fails independently with probability p: (i) contract every edge independently with probability 1-n^{-2\/c}, then (ii) recursively compute the disconnection probability of the resulting tiny graph if each edge fails with probability n^{2\/c}p.\u0026nbsp; We give a short, simple, self-contained proof that this estimator can be computed in linear time and has relative variance O(n^2).\u0026nbsp; Combining these two facts with a relatively standard sparsification argument yields an O(n^3\\log n)-time algorithm for estimating the (un)reliability of a network.\u0026nbsp; We also show how the technique can be used to create unbiased samples of disconnected networks.\u003C\/p\u003E\r\n\r\n\u003Cp\u003ESpeaker\u0026#39;s webpage: \u003Ca href=\u0022http:\/\/people.csail.mit.edu\/karger\/\u0022\u003Ehttp:\/\/people.csail.mit.edu\/karger\/\u003C\/a\u003E\u003Cbr \/\u003E\r\nFall 2016 ARC Seminar Schedule: \u0026nbsp;\u003Ca href=\u0022http:\/\/arc.gatech.edu\/node\/114\u0022 target=\u0022_blank\u0022\u003Ehttp:\/\/arc.gatech.edu\/node\/114\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"A Fast and Simple Unbiased Estimator for Network (Un)reliability (Klaus 1116 E at 11am)"}],"uid":"27466","created_gmt":"2016-08-08 10:29:12","changed_gmt":"2017-04-13 21:15:12","author":"Dani Denton","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2016-09-26T12:00:00-04:00","event_time_end":"2016-09-26T13:00:00-04:00","event_time_end_last":"2016-09-26T13:00:00-04:00","gmt_time_start":"2016-09-26 16:00:00","gmt_time_end":"2016-09-26 17:00:00","gmt_time_end_last":"2016-09-26 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"},{"id":"50875","name":"School of Computer Science"}],"categories":[],"keywords":[{"id":"111051","name":"Algorithm and Randomness Center"},{"id":"4265","name":"ARC"},{"id":"115001","name":"Computational Complexity"},{"id":"114991","name":"Computational Learning Theory"},{"id":"109","name":"Georgia Tech"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"78751","name":"Undergraduate students"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EDani Denton\u003C\/p\u003E\r\n\r\n\u003Cp\u003Edenton at cc dot gatech dot edu\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"560071":{"#nid":"560071","#data":{"type":"event","title":"ARC Colloquium: Ankur Moitra (MIT)","body":[{"value":"\u003Cp style=\u0022color:maroon;\u0022\u003EVideo of this talk is available at: \u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/56016\u0022\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/56016\u003C\/a\u003E\u003C\/p\u003E\r\nFull collection of talk videos are available at:  \r\n\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/a\u003E\r\n\r\n\u003Cbr\u003E\r\n\u003Cbr\u003E\r\n\r\n\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align=\u0022center\u0022\u003E\u003Ca href=\u0022http:\/\/people.csail.mit.edu\/moitra\/\u0022\u003E\u003Cstrong\u003EAnkur Moitra - MIT\u003C\/strong\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EMonday, October 31, 2016\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align=\u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 West \u0026ndash; 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle: \u003C\/strong\u003E\u003Cbr \/\u003E\r\nRobust Statistics, Revisited\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract\u003C\/strong\u003E:\u003Cbr \/\u003E\r\nStarting from the seminal works of Tukey (1960) and Huber (1962), the field of robust statistics asks: Are there estimators that provable work in the presence of noise? The trouble is that all known provably robust estimators are also hard to compute in high-dimensions.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EHere, we study a basic problem in robust statistics, posed in various forms in the above works. Given corrupted samples from a high-dimensional Gaussian, are there efficient algorithms to accurately estimate its parameters? We give the first algorithms that are able to tolerate a constant fraction of corruptions that is independent of the dimension. Additionally, we give several more applications of our techniques to product distributions and various mixture models.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThis is based on joint work with Ilias Diakonikolas, Jerry Li, Gautam Kamath, Daniel Kane and Alistair Stewart.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EBio: \u003C\/strong\u003E\u003Cbr \/\u003E\r\nAnkur Moitra is the Rockwell International Assistant Professor in the Department of Mathematics at MIT and a Principal Investigator in the Computer Science and Artificial Intelligence Lab (CSAIL). The aim of his work is to bridge the gap between theoretical computer science and machine learning by developing algorithms with provable guarantees and foundations for reasoning about their behavior. He is a recipient of a Packard Fellowship, a Sloan Fellowship, an NSF CAREER Award, an NSF Computing and Innovation Fellowship and a Hertz Fellowship.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Revisiting Robust Statistics (Klaus 1116 West at 11am)"}],"uid":"27466","created_gmt":"2016-08-08 10:33:20","changed_gmt":"2017-04-13 21:15:12","author":"Dani Denton","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2016-10-31T12:00:00-04:00","event_time_end":"2016-10-31T13:00:00-04:00","event_time_end_last":"2016-10-31T13:00:00-04:00","gmt_time_start":"2016-10-31 16:00:00","gmt_time_end":"2016-10-31 17:00:00","gmt_time_end_last":"2016-10-31 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"},{"id":"47223","name":"College of Computing"},{"id":"50875","name":"School of Computer Science"}],"categories":[],"keywords":[{"id":"111051","name":"Algorithm and Randomness Center"},{"id":"4265","name":"ARC"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"78751","name":"Undergraduate students"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EDani Denton\u003C\/p\u003E\r\n\r\n\u003Cp\u003Edenton at cc dot gatech dot edu\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}}}