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Dimension-free log-Sobolev inequalities for mixture distributions.

Authors :
Chen, Hong-Bin
Chewi, Sinho
Niles-Weed, Jonathan
Source :
Journal of Functional Analysis. Dec2021, Vol. 281 Issue 11, pN.PAG-N.PAG. 1p.
Publication Year :
2021

Abstract

We prove that if (P x) x ∈ X is a family of probability measures which satisfy the log-Sobolev inequality and whose pairwise chi-squared divergences are uniformly bounded, and μ is any mixing distribution on X , then the mixture ∫ P x d μ (x) satisfies a log-Sobolev inequality. In various settings of interest, the resulting log-Sobolev constant is dimension-free. In particular, our result implies a conjecture of Zimmermann and Bardet et al. that Gaussian convolutions of measures with bounded support enjoy dimension-free log-Sobolev inequalities. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00221236
Volume :
281
Issue :
11
Database :
Academic Search Index
Journal :
Journal of Functional Analysis
Publication Type :
Academic Journal
Accession number :
152710709
Full Text :
https://doi.org/10.1016/j.jfa.2021.109236