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arXiv · 1702.07321

On the convex infimum convolution inequality with optimal cost function

Marta Strzelecka·Michał Strzelecki·Tomasz Tkocz
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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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Marta Strzelecka, Michał Strzelecki, Tomasz Tkocz. 2017-02-23. On the convex infimum convolution inequality with optimal cost function. https://doi.org/10.30757/alea.v14-39

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