On the Law of the Iterated Logarithm in Stochastic Approximation Processes

DOI10.1137/1119097zbMath0333.62053OpenAlexW2079663352MaRDI QIDQ4099096

V. F. Gaposhkin, T. P. Krasulina

Publication date: 1974

Published in: Theory of Probability & Its Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1137/1119097

Mathematics Subject Classification ID

Stochastic approximation (62L20) Large deviations (60F10)

Related Items (12)

On one-sided convergence of a modified stochastic approximation process ⋮ On the interrelation of almost sure invariance principles for certain stochastic adaptive algorithms and for partial sums of random variables ⋮ A Robbins-Monro procedure for estimation in semiparametric regression models ⋮ General multilevel adaptations for stochastic approximation algorithms of Robbins-Monro and Polyak-Ruppert type ⋮ Exact bounds for the rate of convergence in general stochastic approximation procedures ⋮ The Compact Law of the Iterated Logarithm for Multivariate Stochastic Approximation Algorithms ⋮ Asymptotic behavior for the Robbins–Monro process ⋮ A stochastic Newton-Raphson method ⋮ Stochastic approximation algorithms for superquantiles estimation ⋮ On the almost sure asymptotic behaviour of stochastic algorithm ⋮ Strong representation of an adaptive stochastic approximation procedure ⋮ Asymptotic behaviour of a class of stochastic approximation procedures

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