Analysis of practical step size selection in stochastic approximation algorithms

Qi Wang ()

Annals of Operations Research, 2015, vol. 229, issue 1, 759-769

Abstract: For many popular stochastic approximation algorithms, such as the stochastic gradient method and the simultaneous perturbation stochastic approximation method, the practical gain sequence selection is different from the optimal selection, that is theoretically derived from asymptotical performance. We provide formal justification for the reasons why we choose such gain sequence in practice. Copyright Springer Science+Business Media New York 2015

Keywords: Recursive estimation; Stochastic approximation; Practical gain sequences (search for similar items in EconPapers)
Date: 2015
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DOI: 10.1007/s10479-015-1785-9

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