Stochastic First- and Zeroth-Order Methods for Nonconvex Stochastic Programming

In this paper, we introduce a new stochastic approximation type algorithm, namely, the randomized stochastic gradient (RSG) method, for solving an important class of nonlinear (possibly nonconvex) stochastic programming problems. We establish the complexity of this method for computing an approximat...

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Bibliographic Details

Published in:	SIAM journal on optimization Vol. 23; no. 4; pp. 2341 - 2368
Main Authors:	Ghadimi, Saeed, Lan, Guanghui
Format:	Journal Article
Language:	English
Published:	Philadelphia Society for Industrial and Applied Mathematics 01.01.2013
Subjects:	Algorithms Approximation Methods Optimization Random variables Simulation
ISSN:	1052-6234, 1095-7189
Online Access:	Get full text
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