Article first published online: 12 MAY 2015This paper addresses the convergence of simultaneous perturbation stochastic approximation (SPSA) with a norm-limited update vector. We first illustrate an unstable solution of the standard SPSA algorithm which motivates the consideration of a modified version, where the norm of the update vector is limited to a certain value. Next, a result on the almost-sure convergence is presented by reducing the modified algorithm into the standard SPSA algorithm and restricting the probability distribution for the perturbation to a Bernoulli distribution. Finally, we apply the modified algorithm to a system identification problem to demonstrate its performance
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Simultaneous perturbation stochastic approximation (SPSA) algorithms have been found to be very effe...
Discrete stochastic optimization considers the problem of minimizing (or maximizing) loss functions ...
Abstract: The case of SPSA algorithms with two trial simultaneous perturbations is discussed. The be...
We propose a new adaptive algorithm with decreasing step-size for stochastic approximations. The use...
The basics of SPSA (simultaneous perturbation stochastic approximation) initiated and developed by J...
We propose a new adaptive algorithm with decreasing step-size for stochastic approximations. The use...
AbstractWe propose a new adaptive algorithm with decreasing step-size for stochastic approximations....
AbstractResults on the convergence with probability one of stochastic approximation algorithms of th...
Practitioners of iterative optimization techniques want their chosen algorithm to reach the global o...
Four algorithms, all variants of Simultaneous Perturbation Stochastic Approximation (SPSA), are prop...
Simultaneous perturbation stochastic approximation (SPSA) algorithms have been found to be very effe...
A difficulty in using Simultaneous Perturbation Stochastics Approximation (SPSA) is its performance ...
Abstract: Accuracy for main class of Simultaneous Perturbation Stochastic Approximation (SPSA) proce...
Abstract: We show that the Simultaneous Perturbation Stochastic Approximation (SPSA) algorithm with ...
AbstractTo theoretically compare the behavior of different algorithms, compatible performance measur...
Simultaneous perturbation stochastic approximation (SPSA) algorithms have been found to be very effe...
Discrete stochastic optimization considers the problem of minimizing (or maximizing) loss functions ...
Abstract: The case of SPSA algorithms with two trial simultaneous perturbations is discussed. The be...
We propose a new adaptive algorithm with decreasing step-size for stochastic approximations. The use...
The basics of SPSA (simultaneous perturbation stochastic approximation) initiated and developed by J...
We propose a new adaptive algorithm with decreasing step-size for stochastic approximations. The use...
AbstractWe propose a new adaptive algorithm with decreasing step-size for stochastic approximations....
AbstractResults on the convergence with probability one of stochastic approximation algorithms of th...