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» Tensor-Variate Restricted Boltzmann Machines
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JMLR
2010
123views more  JMLR 2010»
13 years 4 months ago
Inductive Principles for Restricted Boltzmann Machine Learning
Recent research has seen the proposal of several new inductive principles designed specifically to avoid the problems associated with maximum likelihood learning in models with in...
Benjamin Marlin, Kevin Swersky, Bo Chen, Nando de ...
NIPS
2008
13 years 11 months ago
Implicit Mixtures of Restricted Boltzmann Machines
We present a mixture model whose components are Restricted Boltzmann Machines (RBMs). This possibility has not been considered before because computing the partition function of a...
Vinod Nair, Geoffrey E. Hinton
ICML
2008
IEEE
14 years 10 months ago
Training restricted Boltzmann machines using approximations to the likelihood gradient
A new algorithm for training Restricted Boltzmann Machines is introduced. The algorithm, named Persistent Contrastive Divergence, is different from the standard Contrastive Diverg...
Tijmen Tieleman
JMLR
2010
125views more  JMLR 2010»
13 years 4 months ago
Stochastic Complexity and Generalization Error of a Restricted Boltzmann Machine in Bayesian Estimation
In this paper, we consider the asymptotic form of the generalization error for the restricted Boltzmann machine in Bayesian estimation. It has been shown that obtaining the maximu...
Miki Aoyagi
NIPS
2008
13 years 11 months ago
The Recurrent Temporal Restricted Boltzmann Machine
The Temporal Restricted Boltzmann Machine (TRBM) is a probabilistic model for sequences that is able to successfully model (i.e., generate nice-looking samples of) several very hi...
Ilya Sutskever, Geoffrey E. Hinton, Graham W. Tayl...