Kesten proposed a method for adjusting the coefficients of a scalar stochastic approximation process, and proved w.p. 1 convergence. A family of multidimensional processes for function minimization are treated here. Each method consists of a sequence of truncated one-dimensional procedures of the Kesten type. The methods seem to offer a number of advantages over the usual Kiefer-Wolfowitz procedures, and are more natural analogs of the schemes in common use in deterministic optimization theory.
Publié le : 1973-09-14
Classification:
Monte-carlo,
sequential analysis,
adaptive process,
stochastic approximation,
sequential optimization with noisy observations
@article{1176342506,
author = {Kushner, H. J. and Gavin, T.},
title = {Extensions of Kesten's Adaptive Stochastic Approximation Method},
journal = {Ann. Statist.},
volume = {1},
number = {2},
year = {1973},
pages = { 851-861},
language = {en},
url = {http://dml.mathdoc.fr/item/1176342506}
}
Kushner, H. J.; Gavin, T. Extensions of Kesten's Adaptive Stochastic Approximation Method. Ann. Statist., Tome 1 (1973) no. 2, pp. 851-861. http://gdmltest.u-ga.fr/item/1176342506/