Modified log-Sobolev inequalities for strongly log-concave distributions

Mary Cryan, Heng Guo, Giorgos Mousa

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We show that the modified log-Sobolev constant for a natural Markov chain which converges to an r-homogeneous strongly log-concave distribution is at least 1/r. Applications include an asymptotically optimal mixing time bound for the bases-exchange walk for matroids, and a concentration bound for Lipschitz functions over these distributions.
Original languageEnglish
Title of host publication2019 IEEE 60th Annual Symposium on Foundations of Computer Science (FOCS)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages1358-1370
Number of pages14
ISBN (Electronic)978-1-7281-4952-3
ISBN (Print)978-1-7281-4953-0
DOIs
Publication statusPublished - 6 Jan 2020
Event60th Annual IEEE Symposium on Foundations of Computer Science - Baltimore, United States
Duration: 9 Nov 201912 Nov 2019
http://focs2019.cs.jhu.edu/

Publication series

Name
ISSN (Print)1523-8288
ISSN (Electronic)2575-8454

Conference

Conference60th Annual IEEE Symposium on Foundations of Computer Science
Abbreviated titleFOCS 2019
CountryUnited States
CityBaltimore
Period9/11/1912/11/19
Internet address

Keywords

  • math.PR
  • cs.DS
  • math.CO

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