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Bibliographic Details
Main Author: Houdré, Christian
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2410.06937
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author Houdré, Christian
author_facet Houdré, Christian
contents Via a covariance representation based on characteristic functions, a known elementary proof of the Gaussian concentration inequality is presented. A few other applications are briefly mentioned.
format Preprint
id arxiv_https___arxiv_org_abs_2410_06937
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle A covariance representation and an elementary proof of the Gaussian concentration inequality
Houdré, Christian
Probability
Machine Learning
60E15, 60G15
Via a covariance representation based on characteristic functions, a known elementary proof of the Gaussian concentration inequality is presented. A few other applications are briefly mentioned.
title A covariance representation and an elementary proof of the Gaussian concentration inequality
topic Probability
Machine Learning
60E15, 60G15
url https://arxiv.org/abs/2410.06937