Improving the Asymptotic Performance of Markov Chain Monte-Carlo by Inserting Vortices
Methodology
2012-09-27 v1
Abstract
We present a new way of converting a reversible finite Markov chain into a non-reversible one, with a theoretical guarantee that the asymptotic variance of the MCMC estimator based on the non-reversible chain is reduced. The method is applicable to any reversible chain whose states are not connected through a tree, and can be interpreted graphically as inserting vortices into the state transition graph. Our result confirms that non-reversible chains are fundamentally better than reversible ones in terms of asymptotic performance, and suggests interesting directions for further improving MCMC.
Keywords
Cite
@article{arxiv.1209.6048,
title = {Improving the Asymptotic Performance of Markov Chain Monte-Carlo by Inserting Vortices},
author = {Yi Sun and Faustino Gomez and Juergen Schmidhuber},
journal= {arXiv preprint arXiv:1209.6048},
year = {2012}
}
Comments
Published in NIPS 2010