Event-driven stochastic approximation

Vivek S. Borkar (), Neeraja Sahasrabudhe () and M. Ashok Vardhan ()
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Vivek S. Borkar: Indian Institute of Technology
Neeraja Sahasrabudhe: Indian Institute of Technology
M. Ashok Vardhan: Indian Institute of Technology

Indian Journal of Pure and Applied Mathematics, 2016, vol. 47, issue 2, 291-299

Abstract: Abstract 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.

Keywords: Stochastic approximation; asynchronous computation; distributed algorithms; o.d.e. limit; sampling bias (search for similar items in EconPapers)
Date: 2016
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DOI: 10.1007/s13226-016-0188-1

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