174 citations · 751 across the 34 of their papers we have counts for
14 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…
Hebbian Synaptic Modifications in Spiking Neurons that Learn
Peter L. Bartlett, Jonathan Baxter
In this paper, we derive a new model of synaptic plasticity, based on recent algorithms for reinforcement learning (in which an agent attempts to learn appropriate actions to maxim…
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…
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…
Bayesian Robustness: A Nonasymptotic Viewpoint
Kush Bhatia, Yi-An Ma, Anca D. Dragan +2
We study the problem of robustly estimating the posterior distribution for the setting where observed data can be contaminated with potentially adversarial outliers. We propose Rob…
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…