Stochastic First-Order Methods with Random Constraint Projection

Stochastic First-Order Methods with Random Constraint Projection

We consider convex optimization problems with structures that are suitable for sequential treatment or online sampling. In particular, we focus on problems where the objective function is an expected value, and the constraint set is the intersection of a large number of simpler sets. We propose an a...

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Bibliographic Details
Main Authors:	Wang, Mengdi, Bertsekas, Dimitri P.
Other Authors:	Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Format:	Article
Language:	en_US
Published:	Society for Industrial and Applied Mathematics (SIAM) 2016
Online Access:	http://hdl.handle.net/1721.1/103776 https://orcid.org/0000-0001-6909-7208

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