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From the 1 of 7 linked papers with an AI index.

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7 papers

stat.CO2026

Wasserstein mixing time of the unadjusted Langevin algorithm

Francesco Pedrotti, Peter A. Whalley

We provide new estimates in Wasserstein distance for the asymptotic bias of the unadjusted Langevin algorithm, in the classical setting of log-smooth strongly log-concave measures.…

math.PR2026

The local product condition implies cutoff

Francesco Pedrotti, Justin Salez

In the theory of mixing times, a famously wrong conjecture predicts that a sequence of Markov processes exhibits cutoff as soon as the product of their Poincaré constant and mixin…

math.PR2026

Entropy-Wasserstein regularization, defective local concentration and a cutoff criterion beyond non-negative curvature

Francesco Pedrotti

Notions of positive curvature have been shown to imply many remarkable properties for Markov processes, in terms, e.g., of regularization effects, functional inequalities, mixing t…

math.PR2025

A transport approach to the cutoff phenomenon

Francesco Pedrotti, Justin Salez

Substantial progress has recently been made in the understanding of the cutoff phenomenon for Markov processes, using an information-theoretic statistics known as varentropy [Sal23…

math.PR2025

-optimal transport of anisotropic log-concave measures and exponential convergence in Fisher's infinitesimal model

Ksenia A. Khudiakova, Jan Maas, Francesco Pedrotti

We prove upper bounds on the -Wasserstein distance from optimal transport between strongly log-concave probability densities and log-Lipschitz perturbations. In the simpl…

math.PR2025

Contractive coupling rates and curvature lower bounds for Markov chains

Francesco Pedrotti

Contractive coupling rates have been recently introduced by Conforti as a tool to establish convex Sobolev inequalities (including modified log-Sobolev and Poincaré inequality) fo…