Add to ORKGThe asymptotic behavior of a distributed, asynchronous stochastic approximation scheme is analyzed in terms of a limiting nonautonomous dierential equation. The relation between the latter and the relative values of suitably rescaled relative frequencies of updates of dierent components is underscored
It is shown here that stability of the stochastic approximation algorithm is implied by the asymptot...
Finding convergence rates for numerical optimization algorithms is an important task, because it giv...
Asynchronous stochastic approximations (SAs) are an important class of model-free algorithms, tools,...
The asymptotic behavior of a distributed, asynchronous stochastic approximation scheme is analyzed i...
The asymptotic behavior of a distributed, asynchronous stochastic approximation scheme is analyzed i...
It is shown here that stability of the stochastic approximation algorithm is implied by the asymptot...
In this paper, we give a generalization of a result by Borkar and Meyn (2000) 1], on the stability a...
We revisit the classical model of Tsitsiklis, Bertsekas and Athans for distributed stochastic approx...
Stochastic approximation is a common paradigm for many stochastic recursions arising both as algorit...
The asymptotic pseudo-trajectory approach to stochastic approximation of Benaïm, Hofbauer and Sorin ...
Bibliography: p. 28-29."November 1984."" ONR/N00014-77-C-532" " NSF-ECS-8217668"John N. Tsitsiklis, ...
Stochastic approximation is a common paradigm for many stochastic recursions arising both as algorit...
In this paper, a distributed stochastic approximation algorithm is studied. Applications of such alg...
It is shown that the stability of the stochastic approximation algorithm is implied by the asymptoti...
Motivated by consensus control of networked systems with communication latency and randomly switchin...
It is shown here that stability of the stochastic approximation algorithm is implied by the asymptot...
Finding convergence rates for numerical optimization algorithms is an important task, because it giv...
Asynchronous stochastic approximations (SAs) are an important class of model-free algorithms, tools,...
The asymptotic behavior of a distributed, asynchronous stochastic approximation scheme is analyzed i...
The asymptotic behavior of a distributed, asynchronous stochastic approximation scheme is analyzed i...
It is shown here that stability of the stochastic approximation algorithm is implied by the asymptot...
In this paper, we give a generalization of a result by Borkar and Meyn (2000) 1], on the stability a...
We revisit the classical model of Tsitsiklis, Bertsekas and Athans for distributed stochastic approx...
Stochastic approximation is a common paradigm for many stochastic recursions arising both as algorit...
The asymptotic pseudo-trajectory approach to stochastic approximation of Benaïm, Hofbauer and Sorin ...
Bibliography: p. 28-29."November 1984."" ONR/N00014-77-C-532" " NSF-ECS-8217668"John N. Tsitsiklis, ...
Stochastic approximation is a common paradigm for many stochastic recursions arising both as algorit...
In this paper, a distributed stochastic approximation algorithm is studied. Applications of such alg...
It is shown that the stability of the stochastic approximation algorithm is implied by the asymptoti...
Motivated by consensus control of networked systems with communication latency and randomly switchin...
It is shown here that stability of the stochastic approximation algorithm is implied by the asymptot...
Finding convergence rates for numerical optimization algorithms is an important task, because it giv...
Asynchronous stochastic approximations (SAs) are an important class of model-free algorithms, tools,...