3 papers
math.PR2026
Entropy contraction of the Gibbs sampler under log-concavity
Filippo Ascolani, Hugo Lavenant, Giacomo Zanella
The Gibbs sampler (a.k.a. Glauber dynamics and heat-bath algorithm) is a popular Markov Chain Monte Carlo algorithm which iteratively samples from the conditional distributions of…
stat.ML2025
Error Bounds and Optimal Schedules for Masked Diffusions with Factorized Approximations
Hugo Lavenant, Giacomo Zanella
Recently proposed generative models for discrete data, such as Masked Diffusion Models (MDMs), exploit conditional independence approximations to reduce the computational cost of p…
stat.ML2024
Convergence rate of random scan Coordinate Ascent Variational Inference under log-concavity
Hugo Lavenant, Giacomo Zanella
The Coordinate Ascent Variational Inference scheme is a popular algorithm used to compute the mean-field approximation of a probability distribution of interest. We analyze its ran…