Abstract #301708

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JSM 2002 Abstract #301708
Activity Number: 273
Type: Topic Contributed
Date/Time: Wednesday, August 14, 2002 : 8:30 AM to 10:20 AM
Sponsor: Section on Statistical Computing*
Abstract - #301708
Title: Convergence of Simultaneous Perturbation Stochastic Approximation for Nondifferentiable Optimization
Author(s): Ying He*+ and Michael Fu+ and Steven Marcus
Affiliation(s): University of Maryland and University of Maryland and University of Maryland
Address: , , , , , , , ,
Keywords: stochastic optimization ; stochastic approximation ; convex analysis ; subgradient ; SPSA ; nondifferentiable optimization
Abstract:

In this paper, we consider Simultaneous Perturbation Stochastic Approximation (SPSA) for function minimization. The standard assumption for convergence is that the function be three times differentiable, although weaker assumptions have been used for special cases. However, all work that we are aware of at least requires differentiability. In this paper, we relax the differentiability requirement and prove convergence using convex analysis.

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