45 search results - page 1 / 9 » Tensor-Variate Restricted Boltzmann Machines |
ACL
2011
13 years 1 months ago
2011
We propose a generative model based on Temporal Restricted Boltzmann Machines for transition based dependency parsing. The parse tree is built incrementally using a shiftreduce pa...
FPGA
2009
ACM
14 years 4 months ago
2009
ACM
Despite the popularity and success of neural networks in research, the number of resulting commercial or industrial applications have been limited. A primary cause of this lack of...
NECO
2008
13 years 9 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...
ICANN
2010
Springer
13 years 10 months ago
2010
Springer
Abstract. Learning algorithms relying on Gibbs sampling based stochastic approximations of the log-likelihood gradient have become a common way to train Restricted Boltzmann Machin...
ESANN
2006
13 years 11 months ago
2006
A probabilistic, ``neural'' approach to sensor modelling and classification is described, performing local data fusion in a wireless system for embedded sensors using a ...