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Modified log-Sobolev inequalities for strongly log-concave distributions

arXiv 1903.06081 ↗First posted 14 Mar 2019math.PR cs.DS math.COcited by 4

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Abstract (arXiv)

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 a sharp mixing time bound for the bases-exchange walk for matroids, and a concentration bound for Lipschitz functions over these distributions.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 14 Mar 2019.

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Citing papers per year: 2022: 1; 2023: 0; 2024: 1; 2025: 1; 2026: 1.

4 papers.

  1. 2022Optimal Sublinear Sampling of Spanning Trees and Determinantal Point Processes via Average-Case Entropic Independencecited by 8
  2. 2025Estimating Ising Models in Total Variation Distancecited by 3
  3. 2024Almost linear time differentially private release of synthetic graphscited by 0
  4. 2026Even Sharper Bounds for Transductive Learning and Its Applicationscited by 0