
The Langevin Monte Carlo algorithm in the non-smooth log-concave case
Lehec, Joseph (2021), The Langevin Monte Carlo algorithm in the non-smooth log-concave case. https://basepub.dauphine.psl.eu/handle/123456789/22285
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Type
Document de travail / Working paperExternal document link
https://hal.archives-ouvertes.fr/hal-03129129Date
2021Series title
Cahier de recherche du CEREMADEPages
19
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We prove non-asymptotic polynomial bounds on the convergence of the Langevin Monte Carlo algorithm in the case where the potential is a convex function which is globally Lipschitz on its domain, typically the maximum of a finite number of affine functions on an arbitrary convex set. In particular the potential is not assumed to be gradient Lipschitz, in contrast with most (if not all) existing works on the topic.Related items
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