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JMLR
2010
139views more  JMLR 2010»
11 years 4 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...
ICML
2010
IEEE
11 years 6 months ago
Particle Filtered MCMC-MLE with Connections to Contrastive Divergence
Learning undirected graphical models such as Markov random fields is an important machine learning task with applications in many domains. Since it is usually intractable to learn...
Arthur Asuncion, Qiang Liu, Alexander T. Ihler, Pa...
ICML
2008
IEEE
12 years 6 months ago
Training restricted Boltzmann machines using approximations to the likelihood gradient
A new algorithm for training Restricted Boltzmann Machines is introduced. The algorithm, named Persistent Contrastive Divergence, is different from the standard Contrastive Diverg...
Tijmen Tieleman
books