5 search results - page 1 / 1 » Wormholes Improve Contrastive Divergence |
NIPS
2003
13 years 5 months ago
2003
In models that define probabilities via energies, maximum likelihood learning typically involves using Markov Chain Monte Carlo to sample from the model’s distribution. If the ...
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...
JMLR
2010
12 years 11 months ago
2010
Composite likelihood methods provide a wide spectrum of computationally efficient techniques for statistical tasks such as parameter estimation and model selection. In this paper,...
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 ...
ICCV
2005
IEEE
13 years 10 months ago
2005
IEEE
We develop a method for learning the spatial statistics of optical flow fields from a novel training database. Training flow fields are constructed using range images of natur...