{"70142":{"#nid":"70142","#data":{"type":"event","title":"CSE Seminar: Alexander Gray","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ECSE\nSeminar: \u003C\/strong\u003E\u003C\/p\u003E\n\n\u003Cp\u003E\u003Cstrong\u003E\u0026nbsp;\u003C\/strong\u003E\u003C\/p\u003E\n\n\u003Cp\u003E\u003Cstrong\u003EBy: \u003C\/strong\u003EAlexander Gray, Associate\nProfessor\u003C\/p\u003E\n\n\u003Cp\u003EComputational Science and Engineering, College of\nComputing, Georgia Tech\u003Cstrong\u003E\u003C\/strong\u003E\u003C\/p\u003E\n\n\u003Cp\u003EDate: Friday, September 23, 2011\u003C\/p\u003E\n\n\u003Cp\u003ETime: 2:00pm - 3:30pm \u003C\/p\u003E\n\n\n\n\u003Cp\u003E\u003Cstrong\u003ELocation:\n\u003C\/strong\u003EKlaus 2447\u003C\/p\u003E\n\n\u003Cp\u003EFor\nmore information please contact\u0026nbsp;Dr. Alex Gray at \u003Ca href=\u0022mailto:agray@cc.gatech.edu\u0022\u003Eagray@cc.gatech.edu\u003C\/a\u003E\u003Cstrong\u003E\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003ETechniques for Massive-Data Machine Learning\u003Cstrong\u003E\u003C\/strong\u003E\u003C\/p\u003E\n\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EStarting\nwith motivations from data analysis problems in astronomy as examples, we\u0027ll\nconsider the task of making\u0026nbsp; state-of-the-art machine learning methods\nscale to massive datasets (including n-point correlation functions, kernel\ndensity estimation, minimum spanning trees, bipartite matching, nonparametric\nBayes classifiers, support vector machines, Nadaraya-Watson regression, kernel\nconditional density estimation, Gaussian process regression, nearest-neighbors,\nprincipal component analysis, hierarchical clustering, and manifold learning),\ndespite their often quadratic or cubic scaling with the number of data, via\nseven different types of computational techniques: indexing, functional\ntransforms, sampling, problem reductions, locality, parallelism, and active\nlearning.\u003Cstrong\u003E\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EAlexander Gray received bachelor\u0027s degrees in Applied Mathematics and Computer\nScience from the University of California, Berkeley and a PhD in Computer\nScience from Carnegie Mellon University, and is currently an Associate\nProfessor in the College of Computing at Georgia Tech. His group of\napproximately 20 researchers, the FASTlab, aims to comprehensively scale up all\nof the major practical methods of machine learning to massive datasets as well\nas develop new statistical methodology and theory, guided by challenge problems\nin cosmology, medicine, and other application areas. He began working with\nmassive scientific datasets in 1993 (long before the current fashionable talk\nof \u201cbig data\u201d) at NASA\u0027s Jet Propulsion Laboratory in its Machine Learning\nSystems Group.\u0026nbsp; High-profile applications of his large-scale ML algorithms\nhave been described in staff written articles in Science and Nature, including\ncontributions to work selected by Science as the Top Scientific Breakthrough of\n2003. He has won or been nominated for a number of best paper awards in\nstatistics and data mining and is a recipient of the National Science\nFoundation CAREER Award in 2009. He gives invited tutorial lectures on\nmassive-scale data analysis at the top data analysis research conferences,\ngovernment agencies, and corporations, and is a member of the prestigious\nNational Academy of Sciences Committee on the Analysis of Massive Data.\u0026nbsp;\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"\u0022Techniques for Massive-Data Machine Learning\u0022"}],"uid":"27174","created_gmt":"2011-09-21 10:23:52","changed_gmt":"2016-10-08 01:55:46","author":"Mike Terrazas","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2011-09-30T15:00:00-04:00","event_time_end":"2011-09-30T16:30:00-04:00","event_time_end_last":"2011-09-30T16:30:00-04:00","gmt_time_start":"2011-09-30 19:00:00","gmt_time_end":"2011-09-30 20:30:00","gmt_time_end_last":"2011-09-30 20:30:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"37041","name":"Computational Science and Engineering"},{"id":"47223","name":"College of Computing"},{"id":"50877","name":"School of Computational Science and Engineering"}],"categories":[],"keywords":[{"id":"14379","name":"alex gray"},{"id":"3497","name":"cse seminar"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:agray@cc.gatech.edu\u0022\u003EAlex Gray\u003C\/a\u003E\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}}}