On the convex infimum convolution inequality with optimal cost function
Probability
2021-05-18 v1 Functional Analysis
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.
Cite
@article{arxiv.1702.07321,
title = {On the convex infimum convolution inequality with optimal cost function},
author = {Marta Strzelecka and Michał Strzelecki and Tomasz Tkocz},
journal= {arXiv preprint arXiv:1702.07321},
year = {2021}
}
Comments
11 pages