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