{"657442":{"#nid":"657442","#data":{"type":"event","title":"PhD Defense by Majid Farhadi","body":[{"value":"\u003Cp\u003ETitle: Randomized Kernel Rounding Methods for Routing, Scheduling, and Machine Learning\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDate: Wednesday, April 20, 2022\u003C\/p\u003E\r\n\r\n\u003Cp\u003ETime: 09:30am EST\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003ELocation: \u003Ca href=\u0022https:\/\/bluejeans.com\/601031659\u0022\u003Ehttps:\/\/bluejeans.com\/601031659\u003C\/a\u003E (online)\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EMajid Farhadi\u003C\/p\u003E\r\n\r\n\u003Cp\u003EPh.D. Candidate\u003C\/p\u003E\r\n\r\n\u003Cp\u003EAlgorithms, Combinatorics, and Optimization School of Computer Science Georgia Institute of Technology\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003ECommittee:\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Swati Gupta, School of Industrial and Systems Engineering, Georgia Institute of Technology Dr. Renato D. C. Monteiro, School of Industrial and Systems Engineering, Georgia Institute of Technology Dr. Mohit Singh, School of Industrial and Systems Engineering, Georgia Institute of Technology Dr. Santosh Vempala, College of Computing, Georgia Institute of Technology\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EAdvisor: Dr. Prasad Tetali, Department of Mathematical Sciences, Carnegie Mellon University\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EReader: Dr. Swati Gupta, School of Industrial and Systems Engineering, Georgia Institute of Technology\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThesis will be available at:\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/drive.google.com\/file\/d\/11e6s2-KEYVaNtrLa1hL4GUyEsm20XQQ5\/view?usp=sharing\u0022\u003Ehttps:\/\/drive.google.com\/file\/d\/11e6s2-KEYVaNtrLa1hL4GUyEsm20XQQ5\/view?usp=sharing\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003ESummary:\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;From Computer Science, Machine Learning, Communications, and Control Systems to Supply Chain, Finance, and Policy Making we make a sequence of choices, optimality of which can be decisive to maximize revenue or critical to ensure robustness, security, and reliability. In numerous cases, solving the exact problem is not feasible, e.g., due to limited computational and storage resources, missing key data, or intrinsic hardness barriers. Therefore, researchers develop algorithms to guarantee solutions that are approximately correct\/optimal.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EWe study classical problems from combinatorial optimization and machine learning and develop near optimal approximation algorithms and computational complexity results. We introduce new randomized techniques, notably the kernel alpha-point rounding, for efficiently converting solutions of tractable convex\/linear relaxations of these problems. The problems under study have immediate applications in machine learning, Ads\/search systems, routing, scheduling, non-convex optimization, mathematical programming, Markov chains, and non-linear dimension reduction; to name but a few. We employ techniques from convex optimization, machine learning, linear algebra, graph theory, high dimensional geometry, combinatorics, and probability theory; and further contribute to such theories, e.g., by providing a new inequality on the lower tail of a sum of Bernoulli random variables.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":" Randomized Kernel Rounding Methods for Routing, Scheduling, and Machine Learning"}],"uid":"27707","created_gmt":"2022-04-19 16:27:13","changed_gmt":"2022-04-19 16:27:13","author":"Tatianna Richardson","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-04-20T10:30:00-04:00","event_time_end":"2022-04-20T12:30:00-04:00","event_time_end_last":"2022-04-20T12:30:00-04:00","gmt_time_start":"2022-04-20 14:30:00","gmt_time_end":"2022-04-20 16:30:00","gmt_time_end_last":"2022-04-20 16:30:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"221981","name":"Graduate Studies"}],"categories":[],"keywords":[{"id":"100811","name":"Phd Defense"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1788","name":"Other\/Miscellaneous"}],"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":""}}}