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SUMMARY:Sketchy decisions: Low-rank convex matrix optimization with optima
 l storage - Joel Tropp (Caltech)
DTSTART:20180618T150000Z
DTEND:20180618T160000Z
UID:TALK103459@talks.cam.ac.uk
CONTACT:Quentin Berthet
DESCRIPTION:Convex matrix optimization problems with low-rank solutions pl
 ay a fundamental role in signal processing\, statistics\, and related disc
 iplines. These problems are difficult to solve because of the cost of main
 taining the matrix decision variable\, even though the low-rank solution h
 as few degrees of freedom. This talk presents an algorithm that provably s
 olves these problems using optimal storage. The algorithm produces high-qu
 ality solutions to large problem instances that\, previously\, were intrac
 table.\n\nJoint work with Volkan Cevher\, Roarke Horstmeyer\, Quoc Tran-Di
 nh\, Madeleine Udell\, and Alp Yurtsever.
LOCATION:MR12
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