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CORR
2008
Springer
121views Education» more  CORR 2008»
13 years 4 months ago
Rate-Distortion via Markov Chain Monte Carlo
We propose an approach to lossy source coding, utilizing ideas from Gibbs sampling, simulated annealing, and Markov Chain Monte Carlo (MCMC). The idea is to sample a reconstructio...
Shirin Jalali, Tsachy Weissman
NAACL
2007
13 years 5 months ago
Bayesian Inference for PCFGs via Markov Chain Monte Carlo
This paper presents two Markov chain Monte Carlo (MCMC) algorithms for Bayesian inference of probabilistic context free grammars (PCFGs) from terminal strings, providing an altern...
Mark Johnson, Thomas L. Griffiths, Sharon Goldwate...
KI
2010
Springer
13 years 2 months ago
Soft Evidential Update via Markov Chain Monte Carlo Inference
The key task in probabilistic reasoning is to appropriately update one’s beliefs as one obtains new information in the form of evidence. In many application settings, however, th...
Dominik Jain, Michael Beetz
AUTOMATICA
2010
122views more  AUTOMATICA 2010»
13 years 4 months ago
Bayesian system identification via Markov chain Monte Carlo techniques
The work here explores new numerical methods for supporting a Bayesian approach to parameter estimation of dynamic systems. This is primarily motivated by the goal of providing ac...
Brett Ninness, Soren J. Henriksen
CISS
2008
IEEE
13 years 10 months ago
Near optimal lossy source coding and compression-based denoising via Markov chain Monte Carlo
— We propose an implementable new universal lossy source coding algorithm. The new algorithm utilizes two wellknown tools from statistical physics and computer science: Gibbs sam...
Shirin Jalali, Tsachy Weissman