15 search results - page 2 / 3 » Learning with Blocks: Composite Likelihood and Contrastive D... |
ICANN
2010
Springer
13 years 6 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...
KES
2006
Springer
13 years 5 months ago
2006
Springer
This paper proposes an English learning support tool which provides users with divergent information to find the right words and expressions. In contrast to a number of software to...
IJCV
2008
13 years 5 months ago
2008
This paper describes two algorithms for the real-time segmentation of foreground from background layers in stereo video sequences. Automatic separation of layers from colour/contr...
JMLR
2010
13 years 3 days ago
2010
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...
JMLR
2010
13 years 3 days 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...