37 search results - page 3 / 8 » Exploring Parallelism in Learning Belief Networks |
JMLR
2010
13 years 1 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...
CHI
2011
ACM
12 years 10 months ago
2011
ACM
Extracting useful knowledge from large network datasets has become a fundamental challenge in many domains, from scientific literature to social networks and the web. We introduc...
JMLR
2010
13 years 1 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...
IJCNN
2007
IEEE
14 years 1 months ago
2007
IEEE
— Fuzzy Cognitive Maps (FCMs) are a class of discrete-time Artificial Neural Networks that are used to model dynamic systems. A recently introduced supervised learning method, wh...
ICML
2010
IEEE
13 years 8 months ago
2010
IEEE
Deep Belief Networks (DBNs) are hierarchical generative models which have been used successfully to model high dimensional visual data. However, they are not robust to common vari...