{"614555":{"#nid":"614555","#data":{"type":"event","title":"PhD Proposal by Samira Samadi","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E Human Aspects of Machine Learning\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003ESamira Samadi\u003C\/p\u003E\r\n\r\n\u003Cp\u003EPh.D. Student\u003C\/p\u003E\r\n\r\n\u003Cp\u003ESchool of Computer Science\u003C\/p\u003E\r\n\r\n\u003Cp\u003ECollege of Computing\u003C\/p\u003E\r\n\r\n\u003Cp\u003EGeorgia Institute of Technology\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022http:\/\/www.samirasamadi.com\/\u0022 target=\u0022_blank\u0022\u003Ehttp:\/\/www.samirasamadi.com\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDate: Thursday, November 29th, 2018\u003C\/p\u003E\r\n\r\n\u003Cp\u003ETime: 9:30am to 11am (EDT)\u003C\/p\u003E\r\n\r\n\u003Cp\u003ELocation: KACB 3402\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ECommittee:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Santosh Vempala (Advisor,\u0026nbsp;School of Computer Science, Georgia Institute of Technology)\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Mohit Singh (School of Computer Science, Georgia Institute of Technology)\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Jamie Morgenstern (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\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EAs humans are inevitably being influenced by machine learning algorithms, it is crucial to study the human aspects of these algorithms. In this proposal, I investigate several ML paradigms from the viewpoint of\u0026nbsp; human usability and fairness. In the first line of work, I present the first usability study of humanly computable password strategies -- mental algorithms proposed by Blum and Vempala to help people calculate, in their heads, passwords for different websites without dependence on third-party tools or external devices. In the second line of work, I study fairness for Principal Component Analysis (PCA), one of the most commonly used dimensionality reduction techniques. We show on real-world data sets that PCA can inadvertently produce low-dimensional representations with different fidelity for two different populations (e.g., men and women). We define the notion of Fair PCA and present a polynomial-time algorithm for finding a low-dimensional representation of the data which is nearly-optimal with respect to this measure. Finally, I will discuss two of my ongoing projects: (a) spectral clustering with the fairness constraint that each population should have approximately equal representation in every cluster, and (b) fair interpretable classifiers for structured outcomes.\u0026nbsp;\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Human Aspects of Machine Learning"}],"uid":"27707","created_gmt":"2018-11-26 16:20:45","changed_gmt":"2018-11-27 18:05:27","author":"Tatianna Richardson","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2018-11-29T09:30:00-05:00","event_time_end":"2018-11-29T23:00:00-05:00","event_time_end_last":"2018-11-29T23:00:00-05:00","gmt_time_start":"2018-11-29 14:30:00","gmt_time_end":"2018-11-30 04:00:00","gmt_time_end_last":"2018-11-30 04:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"221981","name":"Graduate Studies"}],"categories":[],"keywords":[{"id":"102851","name":"Phd proposal"}],"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":""}}}