75 search results - page 5 / 15 » Boltzmann Machines |
ICML
2008
IEEE
15 years 10 months ago
2008
IEEE
Recently, many applications for Restricted Boltzmann Machines (RBMs) have been developed for a large variety of learning problems. However, RBMs are usually used as feature extrac...
ICML
2010
IEEE
14 years 10 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...
87
Voted
ICML
2010
IEEE
14 years 10 months ago
2010
IEEE
Restricted Boltzmann machines were developed using binary stochastic hidden units. These can be generalized by replacing each binary unit by an infinite number of copies that all ...
ICASSP
2010
IEEE
14 years 9 months ago
2010
IEEE
For decades, Hidden Markov Models (HMMs) have been the state-of-the-art technique for acoustic modeling despite their unrealistic independence assumptions and the very limited rep...
JMLR
2010
14 years 4 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...