9 search results - page 1 / 2 » Tempered Markov Chain Monte Carlo for training of Restricted... |
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...
ICML
2005
IEEE
14 years 5 months ago
2005
IEEE
This paper concerns the experimental assessment of tempering as a technique for improving Bayesian inference for C&RT models. Full Bayesian inference requires the computation ...
JMLR
2010
12 years 11 months ago
2010
Markov Random Fields (MRFs) are an important class of probabilistic models which are used for density estimation, classification, denoising, and for constructing Deep Belief Netwo...
UAI
1996
13 years 5 months ago
1996
This paper presents a Bayesian approach to learning the connectivity structure of a group of neurons from data on configuration frequencies. A major objective of the research is t...
ICML
2008
IEEE
14 years 5 months ago
2008
IEEE
Low-rank matrix approximation methods provide one of the simplest and most effective approaches to collaborative filtering. Such models are usually fitted to data by finding a MAP...