On Concentration Inequalities for Vector-Valued Lipschitz Functions
Probability
2021-03-02 v1
Abstract
We derive two upper bounds for the probability of deviation of a vector-valued Lipschitz function of a collection of random variables from its expected value. The resulting upper bounds can be tighter than bounds obtained by a direct application of a classical theorem due to Bobkov and G\"{o}tze.
Cite
@article{arxiv.2103.00651,
title = {On Concentration Inequalities for Vector-Valued Lipschitz Functions},
author = {Dimitrios Katselis and Xiaotian Xie and Carolyn L. Beck and R. Srikant},
journal= {arXiv preprint arXiv:2103.00651},
year = {2021}
}