• xmlui.mirage2.page-structure.header.title
    • français
    • English
  • Help
  • Login
  • Language 
    • Français
    • English
View Item 
  •   BIRD Home
  • CEREMADE (UMR CNRS 7534)
  • CEREMADE : Publications
  • View Item
  •   BIRD Home
  • CEREMADE (UMR CNRS 7534)
  • CEREMADE : Publications
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Browse

BIRDResearch centres & CollectionsBy Issue DateAuthorsTitlesTypeThis CollectionBy Issue DateAuthorsTitlesType

My Account

LoginRegister

Statistics

Most Popular ItemsStatistics by CountryMost Popular Authors
Thumbnail - No thumbnail

Sampling from a log-concave distribution with Projected Langevin Monte Carlo

Bubeck, Sébastien; Eldan, Ronen; Lehec, Joseph (2017), Sampling from a log-concave distribution with Projected Langevin Monte Carlo. https://basepub.dauphine.fr/handle/123456789/17068

Type
Document de travail / Working paper
External document link
https://hal.archives-ouvertes.fr/hal-01428950
Date
2017
Series title
Cahier de recherche CEREMADE, Université Paris-Dauphine
Pages
23
Metadata
Show full item record
Author(s)
Bubeck, Sébastien
Eldan, Ronen
Lehec, Joseph cc
Abstract (EN)
We extend the Langevin Monte Carlo (LMC) algorithm to compactly supported measures via a projection step, akin to projected Stochastic Gradient Descent (SGD). We show that (projected) LMC allows to sample in polynomial time from a log-concave distribution with smooth potential. This gives a new Markov chain to sample from a log-concave distribution. Our main result shows in particular that when the target distribution is uniform, LMC mixes in O(n 7) steps (where n is the dimension). We also provide preliminary experimental evidence that LMC performs at least as well as hit-and-run, for which a better mixing time of O(n 4) was proved by Lovász and Vempala.
Subjects / Keywords
Langevin Monte Carlo algorithm; Stochastic Gradient Descent

Related items

Showing items related by title and author.

  • Thumbnail
    Sampling from a log-concave distribution with Projected Langevin Monte Carlo 
    Bubeck, Sébastien; Eldan, Ronen; Lehec, Joseph (2018) Article accepté pour publication ou publié
  • Thumbnail
    The Langevin Monte Carlo algorithm in the non-smooth log-concave case 
    Lehec, Joseph (2021) Document de travail / Working paper
  • Thumbnail
    Bounding the Norm of a Log-Concave Vector Via Thin-Shell Estimates 
    Eldan, Ronen; Lehec, Joseph (2014) Chapitre d'ouvrage
  • Thumbnail
    Poisson processes and a log-concave Bernstein theorem 
    Klartag, Bo'az; Lehec, Joseph (2019) Article accepté pour publication ou publié
  • Thumbnail
    Circular law for random matrices with unconditional log-concave distribution 
    Adamczak, Radosław; Chafaï, Djalil (2015) Article accepté pour publication ou publié
Dauphine PSL Bibliothèque logo
Place du Maréchal de Lattre de Tassigny 75775 Paris Cedex 16
Phone: 01 44 05 40 94
Contact
Dauphine PSL logoEQUIS logoCreative Commons logo