Projecting Markov Random Field Parameters for Fast Mixing

Markov chain Monte Carlo (MCMC) algorithms are simple and extremely powerful techniques to sample from almost arbitrary distributions. The flaw in practice is that it can take a large and/or unknown amount of time to converge to the stationary distribution. This paper gives sufficient conditions to...

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Veröffentlicht in:	arXiv.org 2014-11
Hauptverfasser:	Liu, Xianghang, Domke, Justin
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Bayesian analysis Divergence Fields (mathematics) Markov analysis Markov chains Monte Carlo simulation Parameters Sampling methods Variational methods
Online-Zugang:	Volltext
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