{"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":""}}}