Event-driven stochastic approximation

被引：0

作者：

Vivek S. Borkar

Neeraja Sahasrabudhe

M. Ashok Vardhan

机构：

[1] Indian Institute of Technology,Department of Electrical Engineering

[2] University of Illinois at Urbana-Champaign,Department of Electrical Engineering

来源：

Indian Journal of Pure and Applied Mathematics | 2016年 / 47卷

关键词：

Stochastic approximation; asynchronous computation; distributed algorithms; o.d.e. limit; sampling bias;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

We consider a Robbins-Monro type iteration wherein noisy measurements are event-driven and therefore arrive asynchronously. We propose a modification of step-sizes that ensures desired asymptotic behaviour regardless of this aspect. This generalizes earlier results on asynchronous stochastic approximation wherein the asynchronous behaviour is across different components, but not along the same component of the vector iteration, as is the case considered here.

引用

页码：291 / 299

页数：8

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