Perturbation theory for Markov chains via Wasserstein distance

v1v2v3 (latest)

Perturbation theory for Markov chains via Wasserstein distance

13 March 2015

Nikolaus Schweizer

ArXiv (abs)PDF HTML

Papers citing "Perturbation theory for Markov chains via Wasserstein distance"

12 / 12 papers shown

Title
Optimal approximating Markov chains for Bayesian inference J. Johndrow Jonathan C. Mattingly Sayan Mukherjee David B. Dunson 60 31 0 13 Aug 2015
On Markov chain Monte Carlo methods for tall data Rémi Bardenet Arnaud Doucet Chris Holmes 71 279 0 11 May 2015
Stability of Noisy Metropolis-Hastings F. Medina-Aguayo Anthony Lee Gareth O. Roberts 105 41 0 24 Mar 2015
Consistency and fluctuations for stochastic gradient Langevin dynamics Yee Whye Teh Alexandre Hoang Thiery Sebastian J. Vollmer 75 235 0 01 Sep 2014
Perfect simulation using atomic regeneration with application to Sequential Monte Carlo Anthony Lee Arnaud Doucet K. Latuszyñski 94 15 0 22 Jul 2014
Ergodicity of Approximate MCMC Chains with Applications to Large Data Sets Natesh S. Pillai Aaron Smith 67 59 0 01 May 2014
Austerity in MCMC Land: Cutting the Metropolis-Hastings Budget Anoop Korattikara Yutian Chen Max Welling 73 244 0 19 Apr 2013
Error bounds for Metropolis-Hastings algorithms applied to perturbations of Gaussian measures in high dimensions A. Eberle 94 41 0 03 Oct 2012
Bayesian Posterior Sampling via Stochastic Gradient Fisher Scoring S. Ahn Anoop Korattikara Balan Max Welling 77 306 0 27 Jun 2012
Spectral gaps for a Metropolis-Hastings algorithm in infinite dimensions Martin Hairer Andrew M. Stuart Sebastian J. Vollmer 100 188 0 06 Dec 2011
Quantitative bounds for Markov chain convergence: Wasserstein and total variation distances N. Madras Deniz Sezer 77 54 0 25 Feb 2011
Approximate Bayesian Computational methods Jean-Michel Marin Pierre Pudlo Christian P. Robert Robin J. Ryder 224 866 0 05 Jan 2011