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SUMMARY:Connections between Optimization\, Learning and Control: Past\, Pr
 esent and Future
DTSTART:20210614T161000
DTEND:20210614T171000
DTSTAMP:20260407T064453Z
UID:4d5745d3117bd0d9db0c24f0dbbcfc4d8d72cf0139b585a972538b49
CATEGORIES:Conferences - Seminars
DESCRIPTION:Prof. Stephen Wright\nAs part of the summer school "Foundation
 s and mathematical guarantees of data-driven control"\, we would like to a
 nnounce the talk by Prof. Stephen Wright entitled "Connections between Opt
 imization\, Learning and Control: Past\, Present and Future".\n\nAbstract:
  Optimization\, learning\, and control are interconnected disciplines\, en
 riching each other with the complementary perspectives that they provide o
 n many problems and issues. We start by tracing the historical engagement 
 of optimization with control and learning\, leading to the present situati
 on in which optimization methods play a central role in such areas as deep
  neural networks\, low-rank matrix problems\, and model predictive control
 . We present some recent results on the use of neural networks in process 
 control\, and discuss the ways in which control and learning have influenc
 ed core optimization research. Finally we speculate on some possible futur
 e arenas of engagement between these areas.
LOCATION:https://epfl.zoom.us/j/62746824090?pwd=bTNKT1JyVTZrTkw4MyswcWV5Vj
 dvdz09
STATUS:CONFIRMED
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