115 citations · 307 across the 11 of their papers we have counts for
13 papers
A fast asynchronous MCMC sampler for sparse Bayesian inference
Yves Atchadé, Liwei Wang
We propose a very fast approximate Markov Chain Monte Carlo (MCMC) sampling framework that is applicable to a large class of sparse Bayesian inference problems, where the computati…
Markov chain Monte Carlo algorithms with sequential proposals
Joonha Park, Yves F. Atchadé
We explore a general framework in Markov chain Monte Carlo (MCMC) sampling where sequential proposals are tried as a candidate for the next state of the Markov chain. This sequenti…
Approximate spectral gaps for Markov chains mixing times in high dimensions
Yves F. Atchadé
This paper introduces a concept of approximate spectral gap to analyze the mixing time of Markov Chain Monte Carlo (MCMC) algorithms for which the usual spectral gap is degenerate…
Bayesian variable selection in linear regression models with instrumental variables
Gautam Sabnis, Yves Atchadé, Prosper Dovonon
Many papers on high-dimensional statistics have proposed methods for variable selection and inference in linear regression models by relying explicitly or implicitly on the assumpt…
Unbiased Markov chain Monte Carlo with couplings
Pierre E. Jacob, John O'Leary, Yves F. Atchadé
Markov chain Monte Carlo (MCMC) methods provide consistent of integrals as the number of iterations goes to infinity. MCMC estimators are generally biased after any fixed number of…
Scalable Computation of Regularized Precision Matrices via Stochastic Optimization
Yves F. Atchadé, Rahul Mazumder, Jie Chen
We consider the problem of computing a positive definite inverse covariance matrix aka precision matrix which optimizes a regularized Gaussian maximum lik…