396 search results - page 7 / 80 » On the Use of Restrictions for Learning Bayesian Networks |
FPL
2009
Springer
14 years 15 hour ago
2009
Springer
Restricted Boltzmann Machines (RBMs) — the building block for newly popular Deep Belief Networks (DBNs) — are a promising new tool for machine learning practitioners. However,...
CVPR
2009
IEEE
15 years 2 months ago
2009
IEEE
In this paper we present a method for learning classspecific
features for recognition. Recently a greedy layerwise
procedure was proposed to initialize weights of deep
belief ne...
ICML
2008
IEEE
14 years 8 months ago
2008
IEEE
Bayesian network classifiers have been widely used for classification problems. Given a fixed Bayesian network structure, parameters learning can take two different approaches: ge...
ASC
2006
13 years 7 months ago
2006
For some time, learning Bayesian networks has been both feasible and useful in many problems domains. Recently research has been done on learning equivalence classes of Bayesian n...
NN
1997
Springer
13 years 11 months ago
1997
Springer
Bayesian networks are directed acyclic graphs that represent dependencies between variables in a probabilistic model. Many time series models, including the hidden Markov models (H...