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May 2021 Stochastic Approximation: From Statistical Origin to Big-Data, Multidisciplinary Applications
Tze Leung Lai, Hongsong Yuan
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Statist. Sci. 36(2): 291-302 (May 2021). DOI: 10.1214/20-STS784

Abstract

Stochastic approximation was introduced in 1951 to provide a new theoretical framework for root finding and optimization of a regression function in the then-nascent field of statistics. This review shows how it has evolved in response to other developments in statistics, notably time series and sequential analysis, and to applications in artificial intelligence, economics and engineering. Its resurgence in the big data era has led to new advances in both theory and applications of this microcosm of statistics and data science.

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Tze Leung Lai. Hongsong Yuan. "Stochastic Approximation: From Statistical Origin to Big-Data, Multidisciplinary Applications." Statist. Sci. 36 (2) 291 - 302, May 2021. https://doi.org/10.1214/20-STS784

Information

Published: May 2021
First available in Project Euclid: 19 April 2021

Digital Object Identifier: 10.1214/20-STS784

Keywords: control , gradient boosting , optimization , recursive stochastic algorithms , regret , weak greedy variable selection

Rights: Copyright © 2021 Institute of Mathematical Statistics

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Vol.36 • No. 2 • May 2021
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