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SUMMARY:Amir Beck (Tel-Aviv University)
DTSTART:20200907T133000Z
DTEND:20200907T143000Z
DTSTAMP:20260423T021005Z
UID:OWOS/16
DESCRIPTION:Title: <a href="https://researchseminars.org/talk/OWOS/16/">Du
 al Randomized Coordinate Descent Method for Solving a Class of Nonconvex P
 roblems</a>\nby Amir Beck (Tel-Aviv University) as part of One World Optim
 ization seminar\n\n\nAbstract\nWe consider a nonconvex optimization proble
 m consisting of maximizing the difference of two convex functions. We pres
 ent a randomized method that requires low computational effort at each ite
 ration. The described method is a randomized coordinate descent method emp
 loyed on the so-called Toland-dual problem. We prove subsequence convergen
 ce to dual stationarity points\, a new notion that we introduce and shown 
 to be tighter than the standard criticality. Almost sure rate of convergen
 ce of an optimality measure of the  dual sequence is proven. We demonstrat
 e the potential of our results on three Principal Component Analysis (PCA)
  models resulting in extremely simple algorithms\nJoint work Marc Teboulle
 \n\nthe address and password of the zoom room of the seminar are sent by e
 -mail on the mailinglist of the seminar one day before each talk\n
LOCATION:https://researchseminars.org/talk/OWOS/16/
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