37 search results - page 4 / 8 » A Fast Learning Algorithm for Deep Belief Nets |
JMLR
2010
13 years 2 months ago
2010
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...
JMLR
2010
13 years 2 months ago
2010
Much recent research has been devoted to learning algorithms for deep architectures such as Deep Belief Networks and stacks of auto-encoder variants, with impressive results obtai...
ICML
2010
IEEE
13 years 8 months ago
2010
IEEE
Deep Belief Networks (DBNs) are hierarchical generative models which have been used successfully to model high dimensional visual data. However, they are not robust to common vari...
CIMCA
2005
IEEE
14 years 1 months ago
2005
IEEE
We give a fast and practical algorithm for statistical learning hyperparameters from observable data in probabilistic image processing, which is based on Gaussian graphical model ...
ICML
2010
IEEE
13 years 8 months ago
2010
IEEE
When modeling high-dimensional richly structured data, it is often the case that the distribution defined by the Deep Boltzmann Machine (DBM) has a rough energy landscape with man...