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UID:20260806T093717EDT-4353usuAP5@132.216.98.100
DTSTAMP:20260806T133717Z
DESCRIPTION:A variational perspective for accelerated methods in optimizati
 onAbstract:\n	Accelerated gradient methods play a central role in optimizat
 ion\, achieving optimal rates in many settings. While many generalizations
  and extensions of Nesterov's original acceleration method have been propo
 sed\, it is not yet clear what is the natural scope of the acceleration co
 ncept. In this work\, we study accelerated methods from a continuous-time 
 perspective. We show that there is a Lagrangian functional that we call th
 e “Bregman Lagrangian” which generates a large class of accelerated method
 s in continuous time\, including (but not limited to) accelerated gradient
  descent\, its non-Euclidean extension\, and accelerated higher-order grad
 ient methods. We show that the continuous-time limit of all of these metho
 ds correspond to traveling the same curve in spacetime at different speeds
 . From this perspective\, Nesterov's technique and many of its generalizat
 ions can be viewed as a systematic way to go from the continuous-time curv
 es generated by the Bregman Lagrangian to a family of discrete-time accele
 rated algorithms.\n	 \n
DTSTART:20161017T190000Z
DTEND:20161017T200000Z
LOCATION:Room 920\, Burnside Hall\, CA\, QC\, Montreal\, H3A 0B9\, 805 rue 
 Sherbrooke Ouest
SUMMARY:Andre Wibisono (University of Wisconsin-Madison)
URL:/channels/event/andre-wibisono-university-wisconsi
 n-madison-263437
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