Bounding d̄-distance by informational divergence: A method to prove measure concentration

173Citations
Citations of this article
15Readers
Mendeley users who have this article in their library.

Abstract

There is a simple inequality by Pinsker between variational distance and informational divergence of probability measures defined on arbitrary probability spaces. We shall consider probability measures on sequences taken from countable alphabets, and derive, from Pinsker's inequality, bounds on the d̄-distance by informational divergence. Such bounds can be used to prove the "concentration of measure" phenomenon for some non product distributions.

Cite

CITATION STYLE

APA

Marton, K. (1996). Bounding d̄-distance by informational divergence: A method to prove measure concentration. Annals of Probability, 24(2), 857–866. https://doi.org/10.1214/aop/1039639365

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free