538 citations · 1.8k across the 55 of their papers we have counts for
8 papers · 1 filter
Sampling for Bayesian Mixture Models: MCMC with Polynomial-Time Mixing
Wenlong Mou, Nhat Ho, Martin J. Wainwright +2
We study the problem of sampling from the power posterior distribution in Bayesian Gaussian mixture models, a robust version of the classical posterior. This power posterior is kno…
An Efficient Sampling Algorithm for Non-smooth Composite Potentials
Wenlong Mou, Nicolas Flammarion, Martin J. Wainwright +1
We consider the problem of sampling from a density of the form , where is a smooth and strongly convex func…
Instance-dependent -bounds for policy evaluation in tabular reinforcement learning
Ashwin Pananjady, Martin J. Wainwright
Markov reward processes (MRPs) are used to model stochastic phenomena arising in operations research, control engineering, robotics, and artificial intelligence, as well as communi…
High-Order Langevin Diffusion Yields an Accelerated MCMC Algorithm
Wenlong Mou, Yi-An Ma, Martin J. Wainwright +2
We propose a Markov chain Monte Carlo (MCMC) algorithm based on third-order Langevin dynamics for sampling from distributions with log-concave and smooth densities. The higher-orde…
Improved Bounds for Discretization of Langevin Diffusions: Near-Optimal Rates without Convexity
Wenlong Mou, Nicolas Flammarion, Martin J. Wainwright +1
We present an improved analysis of the Euler-Maruyama discretization of the Langevin diffusion. Our analysis does not require global contractivity, and yields polynomial dependence…
Stochastic approximation with cone-contractive operators: Sharp -bounds for -learning
Martin J. Wainwright
Motivated by the study of -learning algorithms in reinforcement learning, we study a class of stochastic approximation procedures based on operators that satisfy monotonicity an…