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UID:2387@i2m.univ-amu.fr
DTSTART;TZID=Europe/Paris:20180615T140000
DTEND;TZID=Europe/Paris:20180615T150000
DTSTAMP:20180531T120000Z
URL:https://www.i2m.univ-amu.fr/evenements/generic-acceleration-schemes-fo
 r-gradient-based-optimization/
SUMMARY: (...): Generic acceleration schemes for gradient-based optimizatio
 n
DESCRIPTION:: In this talk\, we present generic techniques to accelerate gr
 adient-based optimization algorithms. These approaches build upon the inex
 act proximal point algorithm for minimizing a convex objective function\, 
 and consists of approximately solving a sequence of well-chosen auxiliary 
 subproblems\, leading to faster convergence for the original problem. We i
 ntroduce two variants based on Nesterov's acceleration and Quasi-Newton pr
 inciples\, respectively. One of the key to achieve acceleration in theory 
 and in practice is to solve these sub-problems with appropriate accuracy b
 y using the right stopping criterion and the right warm-start strategy.htt
 p://lear.inrialpes.fr/people/mairal/
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DTSTART:20180325T030000
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