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Dimension-free log-Sobolev inequalities for mixture distributions.
- 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]
- Subjects :
- *GAUSSIAN measures
*PROBABILITY measures
Subjects
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