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NAACL
2007
13 years 7 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...
TCOM
2010
138views more  TCOM 2010»
13 years 4 months ago
Approaching MIMO capacity using bitwise Markov Chain Monte Carlo detection
—This paper examines near capacity performance of Markov Chain Monte Carlo (MCMC) detectors for multipleinput and multiple-output (MIMO) channels. The proposed MCMC detector (Log...
Rong-Rong Chen, Ronghui Peng, Alexei Ashikhmin, Be...
JMLR
2010
139views more  JMLR 2010»
13 years 25 days ago
Tempered Markov Chain Monte Carlo for training of Restricted Boltzmann Machines
Alternating Gibbs sampling is the most common scheme used for sampling from Restricted Boltzmann Machines (RBM), a crucial component in deep architectures such as Deep Belief Netw...
Guillaume Desjardins, Aaron C. Courville, Yoshua B...
ECCV
2002
Springer
14 years 8 months ago
A Markov Chain Monte Carlo Approach to Stereovision
We propose Markov chain Monte Carlo sampling methods to address uncertainty estimation in disparity computation. We consider this problem at a postprocessing stage, i.e. once the d...
Julien Sénégas
IOR
2008
91views more  IOR 2008»
13 years 6 months ago
A Randomized Quasi-Monte Carlo Simulation Method for Markov Chains
We introduce and study a randomized quasi-Monte Carlo method for estimating the state distribution at each step of a Markov chain. The number of steps in the chain can be random an...
Pierre L'Ecuyer, Christian Lécot, Bruno Tuf...