{"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":""}}}