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...
A new algorithm for training Restricted Boltzmann Machines is introduced. The algorithm, named Persistent Contrastive Divergence, is different from the standard Contrastive Diverg...
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 ...
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...
Jessica H. Fong, Anna C. Gilbert, Sampath Kannan, ...