General multilevel adaptations for stochastic approximation algorithms II: CLTs

Steffen Dereich

Stochastic Processes and their Applications, 2021, vol. 132, issue C, 226-260

Abstract: In this article we establish central limit theorems for multilevel Polyak–Ruppert averaged stochastic approximation schemes. We work under very mild technical assumptions and consider the slow regime in which typical errors decay like N−δ with δ∈(0,12) and the critical regime in which errors decay of order N−1∕2logN in the runtime N of the algorithm.

Keywords: Stochastic approximation; Multilevel Monte Carlo; Ruppert–Polyak average; Central limit theorem; Stable convergence (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:spapps:v:132:y:2021:i:c:p:226-260

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DOI: 10.1016/j.spa.2020.11.001

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