Variations and extensions of the Gaussian concentration inequality, Part I
Probability
2022-05-16 v3
Abstract
The classical Gaussian concentration inequality for Lipschitz functions is adapted to a setting where the classical assumptions (i.e. Lipschitz and Gaussian) are not met. The theory is more direct than much of the existing theory designed to handle related generalizations. An application is presented to linear combinations of heavy tailed random variables.
Keywords
Cite
@article{arxiv.1812.10938,
title = {Variations and extensions of the Gaussian concentration inequality, Part I},
author = {Daniel J. Fresen},
journal= {arXiv preprint arXiv:1812.10938},
year = {2022}
}
Comments
18 pages. The original arXiv version has been split into two separate papers, Part I and Part II; this is Part I. To appear in Quaest. Math