Using Fast Weights to Improve Persistent Contrastive Divergence
Published on Aug 26, 20097817 Views
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 iterations to get