Add to ORKGThe basics of SPSA (simultaneous perturbation stochastic approximation) initiated and developed by J.C. Spall in his 1992 IEEE Trans. Automat. Contr. paper will be desctribed. We point out the advantages of SPSA over the finite difference stochastic approximation (FDSA) or Kiefer-Wolfowitz (KW) method. Its applicability in noise free optimization and in discrete optimization will be also briefly described
This paper addresses the optimisation of particle filtering methods aka Sequential Monte Carlo (SMC)...
We analyze the use of simultaneous perturbation stochastic approximation (SPSA), a stochastic optimi...
We study PCA as a stochastic optimization problem and propose a novel stochastic approximation algor...
Practitioners of iterative optimization techniques want their chosen algorithm to reach the global o...
Abstract: The case of SPSA algorithms with two trial simultaneous perturbations is discussed. The be...
A difficulty in using Simultaneous Perturbation Stochastics Approximation (SPSA) is its performance ...
Four algorithms, all variants of Simultaneous Perturbation Stochastic Approximation (SPSA), are prop...
Discrete stochastic optimization considers the problem of minimizing (or maximizing) loss functions ...
Abstract: We show that the Simultaneous Perturbation Stochastic Approximation (SPSA) algorithm with ...
In this paper a novel application of the simultaneous perturbation stochastic approximation algorith...
Simultaneous perturbation stochastic approximation (SPSA) algorithms have been found to be very effe...
Article first published online: 12 MAY 2015This paper addresses the convergence of simultaneous pert...
Abstract: Accuracy for main class of Simultaneous Perturbation Stochastic Approximation (SPSA) proce...
Abstract — The estimates of the al-gorithm of the simultaneously per-turbation stochastic approximat...
Simultaneous perturbation stochastic approximation (SPSA) algorithms have been found to be very effe...
This paper addresses the optimisation of particle filtering methods aka Sequential Monte Carlo (SMC)...
We analyze the use of simultaneous perturbation stochastic approximation (SPSA), a stochastic optimi...
We study PCA as a stochastic optimization problem and propose a novel stochastic approximation algor...
Practitioners of iterative optimization techniques want their chosen algorithm to reach the global o...
Abstract: The case of SPSA algorithms with two trial simultaneous perturbations is discussed. The be...
A difficulty in using Simultaneous Perturbation Stochastics Approximation (SPSA) is its performance ...
Four algorithms, all variants of Simultaneous Perturbation Stochastic Approximation (SPSA), are prop...
Discrete stochastic optimization considers the problem of minimizing (or maximizing) loss functions ...
Abstract: We show that the Simultaneous Perturbation Stochastic Approximation (SPSA) algorithm with ...
In this paper a novel application of the simultaneous perturbation stochastic approximation algorith...
Simultaneous perturbation stochastic approximation (SPSA) algorithms have been found to be very effe...
Article first published online: 12 MAY 2015This paper addresses the convergence of simultaneous pert...
Abstract: Accuracy for main class of Simultaneous Perturbation Stochastic Approximation (SPSA) proce...
Abstract — The estimates of the al-gorithm of the simultaneously per-turbation stochastic approximat...
Simultaneous perturbation stochastic approximation (SPSA) algorithms have been found to be very effe...
This paper addresses the optimisation of particle filtering methods aka Sequential Monte Carlo (SMC)...
We analyze the use of simultaneous perturbation stochastic approximation (SPSA), a stochastic optimi...
We study PCA as a stochastic optimization problem and propose a novel stochastic approximation algor...