Smoothed First-order Algorithms for Expectation-valued Constrained Problems

Afrooz Jalilzadeh, Vinayak V. Shanbhag

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We consider the development of first-order algorithms for convex stochastic optimization problems with expectation constraints. By recasting the problem as a solution to a monotone stochastic variational inequality problem, we note that a solution to this problem can be obtained as a solution to an unconstrained nonsmooth convex stochastic optimization problem. We utilize a variance-reduced smoothed first-order scheme for resolving such a problem and derive rate statements for such a scheme.

Original languageEnglish (US)
Title of host publication2019 53rd Annual Conference on Information Sciences and Systems, CISS 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728111513
DOIs
StatePublished - Apr 16 2019
Event53rd Annual Conference on Information Sciences and Systems, CISS 2019 - Baltimore, United States
Duration: Mar 20 2019Mar 22 2019

Publication series

Name2019 53rd Annual Conference on Information Sciences and Systems, CISS 2019

Conference

Conference53rd Annual Conference on Information Sciences and Systems, CISS 2019
CountryUnited States
CityBaltimore
Period3/20/193/22/19

All Science Journal Classification (ASJC) codes

  • Information Systems

Cite this

Jalilzadeh, A., & Shanbhag, V. V. (2019). Smoothed First-order Algorithms for Expectation-valued Constrained Problems. In 2019 53rd Annual Conference on Information Sciences and Systems, CISS 2019 [8692925] (2019 53rd Annual Conference on Information Sciences and Systems, CISS 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CISS.2019.8692925