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DTSTART:20170312T070000
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DTSTART;TZID=America/Detroit:20170407T113000
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DTSTAMP:20221210T050355
CREATED:20170404T134314Z
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SUMMARY:Statistics Department Seminar Series: Joel Tropp\, PhD\, Cal Tech
DESCRIPTION:\nJoel Tropp\, PhD\nProfessor of Applied & Computational Mathematics\nCalifornia Institute of Technology\n \n‘Sketchy Decisions: Low-rank Matrix Optimization with Optimal Storage’\nAbstract: Convex matrix optimization problems with low-rank solutions play a fundamental role in signal processing\, statistics\, and related disciplines. These problems are difficult to solve because of the cost of maintaining the matrix decision variable\, even though the low-rank solution has few degrees of freedom. This talk presents the first algorithm that provably solves these problems using optimal storage. The algorithm produces high-quality solutions to large problem instances that\, previously\, were intractable. \nJoint with Volkan Cevher\, Roarke Horstmeyer\, Quoc Tran-Dinh\, Madeleine Udell\, and Alp Yurtsever. \nBio: My research identifies situations where sparse approximation problems can be solved using efficient computational algorithms. In particular\, I have analyzed the performance of greedy pursuit methods\, which are popular with practitioners because of their speed. I have also developed a substantial body of results for techniques based on convex programming. A third strand of work addresses the tractability of random instances of sparse approximation. This research has yielded new results on the behavior of random matrices. \nWelcome Reception at 11:00 a.m.\n \n
URL:https://midas.umich.edu/event/statistics-department-seminar-series-joel-tropp-phd-cal-tech/
LOCATION:Room 411 West Hall\, 1085 S University Ave\, Ann Arbor\, MI\, 48109\, United States
ORGANIZER;CN="Kaylee%20Shelton":MAILTO:kshelto@umich.edu
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