Global Random Optimization by Simultaneous Perturbation Stochastic Approximation
نویسندگان
چکیده
منابع مشابه
Convergence of simultaneous perturbation stochastic approximation for nondifferentiable optimization
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 requireme...
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The simultaneous perturbation stochastic approximation (SPSA) algorithm has recently attracted considerable attention for optimization problems where it is di cult or impossible to obtain a direct gradient of the objective (say, loss) function. The approach is based on a highly e cient simultaneous perturbation approximation to the gradient based on loss function measurements. SPSA is based on ...
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ژورنال
عنوان ژورنال: IEEE Transactions on Automatic Control
سال: 2008
ISSN: 0018-9286
DOI: 10.1109/tac.2008.917738