206 search results - page 3 / 42 » Classification using discriminative restricted Boltzmann mac... |
JMLR
2010
12 years 12 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...
FPL
2009
Springer
13 years 9 months ago
2009
Springer
Although there are many neural network FPGA architectures, there is no framework for designing large, high-performance neural networks suitable for the real world. In this paper, ...
NECO
2008
13 years 5 months ago
2008
Deep Belief Networks (DBN) are generative neural network models with many layers of hidden explanatory factors, recently introduced by Hinton et al., along with a greedy layer-wis...
ICML
2007
IEEE
14 years 5 months ago
2007
IEEE
Most of the existing approaches to collaborative filtering cannot handle very large data sets. In this paper we show how a class of two-layer undirected graphical models, called R...
ICML
2010
IEEE
13 years 6 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 ...