{"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":""}}}