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SUMMARY:Adaptive Sampling for Constrained Optimization under Uncertainty
DTSTART:20221114T161500
DTEND:20221114T171500
DTSTAMP:20260501T114324Z
UID:2ae04d25c1c4d2d4ae9da984ee0dfc317308e3ea3d7cbfd87abfe8dd
CATEGORIES:Conferences - Seminars
DESCRIPTION:Brendan Keith (Brown University)\nStochastic optimization prob
 lems with deterministic constraints commonly appear in machine learning\, 
 finance\, and engineering applications. This talk presents an improved ada
 ptive solution strategy for this important class of problems. The aim is t
 o decrease the computational cost while maintaining an optimal convergence
  rate. The guiding principle is to adjust the batch size (or sample size) 
 on the fly so that the error in the gradient approximation remains proport
 ional to the error in the underlying optimization problem. After providing
  motivation and context\, I will present new adaptive sampling algorithms 
 that simultaneously maintain optimal sample efficiency and iteration compl
 exity for risk-neutral and risk-averse optimization under uncertainty with
  deterministic constraints. I will then demonstrate the efficacy of these 
 algorithms in multiple applications\, drawing mainly from use cases found 
 in engineering design. This talk will provide an introduction to adaptive 
 sampling that aims to be accessible to a broad audience as well as showcas
 e ongoing work in collaboration with Lawrence Livermore National Laborator
 y and UT Austin.\n\nBio: Brendan Keith is an Assistant Professor in the Di
 vision of Applied Mathematics at Brown University in Providence\, Rhode Is
 land. His research interests are mainly related to the modeling and simula
 tion of problems arising in natural sciences and engineering\, focusing on
  numerical methods for partial differential equations\, scientific machine
  learning\, and PDE-constrained optimization. In 2018\, Brendan received h
 is Ph.D. in Computational Science\, Engineering\, and Mathematics from the
  Oden Institute for Computational Engineering and Sciences at the Universi
 ty of Texas at Austin. He has held postdoctoral positions at TU Munich\, I
 CERM\, and Lawrence Livermore National Laboratory.
LOCATION:GA 3 21 https://plan.epfl.ch/?room==GA%203%2021
STATUS:CONFIRMED
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