On the convex infimum convolution inequality with optimal cost function (1702.07321v1)

Published 23 Feb 2017 in math.PR and math.FA

Abstract: We show that every symmetric random variable with log-concave tails satisfies the convex infimum convolution inequality with an optimal cost function (up to scaling). As a result, we obtain nearly optimal comparison of weak and strong moments for symmetric random vectors with independent coordinates with log-concave tails.

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