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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…
stat.ML2024
Robust Approximate Sampling via Stochastic Gradient Barker Dynamics
Lorenzo Mauri, Giacomo Zanella
Stochastic Gradient (SG) Markov Chain Monte Carlo algorithms (MCMC) are popular algorithms for Bayesian sampling in the presence of large datasets. However, they come with little t…