3 search results - page 1 / 1 » Empirical Analysis of the Divergence of Gibbs Sampling Based... |
ICANN
2010
Springer
13 years 5 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...
JMLR
2010
12 years 11 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
12 years 11 months ago
2010
Composite likelihood methods provide a wide spectrum of computationally efficient techniques for statistical tasks such as parameter estimation and model selection. In this paper,...