随机逼近:从统计起源到大数据，多学科应用

IF 3.9 1区数学 Q1 STATISTICS & PROBABILITY

Statistical Science Pub Date : 2021-04-01 DOI:10.1214/20-STS784

T. Lai, Hongsong Yuan

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引用次数: 3

摘要

随机近似于1951年被引入，为回归函数的寻根和优化提供了一个新的理论框架。这篇综述展示了它是如何随着统计学的其他发展而发展的，特别是时间序列和序列分析，以及它在人工智能、经济学和工程学中的应用。它在大数据时代的复苏导致了这一统计学和数据科学微观世界的理论和应用的新进展。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Stochastic Approximation: From Statistical Origin to Big-Data, Multidisciplinary Applications

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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来源期刊

Statistical Science 数学-统计学与概率论

CiteScore

6.50

自引率

1.80%

发文量

审稿时长

>12 weeks

期刊介绍： The central purpose of Statistical Science is to convey the richness, breadth and unity of the field by presenting the full range of contemporary statistical thought at a moderate technical level, accessible to the wide community of practitioners, researchers and students of statistics and probability.