4 search results - page 1 / 1 » Using fast weights to improve persistent contrastive diverge... |
ICML
2009
IEEE
13 years 11 months ago
2009
IEEE
The most commonly used learning algorithm for restricted Boltzmann machines is contrastive divergence which starts a Markov chain at a data point and runs the chain for only a few...
ICML
2008
IEEE
14 years 5 months ago
2008
IEEE
A new algorithm for training Restricted Boltzmann Machines is introduced. The algorithm, named Persistent Contrastive Divergence, is different from the standard Contrastive Diverg...
CVPR
2009
IEEE
14 years 11 months ago
2009
IEEE
Many computer vision problems can be formulated in
a Bayesian framework with Markov Random Field (MRF)
or Conditional Random Field (CRF) priors. Usually, the
model assumes that ...
ALGORITHMICA
2005
13 years 4 months ago
2005
The current standard for intra-domain network routing, Open Shortest Path First (OSPF), suffers from a number of problems--the tunable parameters (the weights) are hard to optimiz...