UAI
2003
13 years 6 months ago
2003
Continuous time Bayesian networks (CTBN) describe structured stochastic processes with finitely many states that evolve over continuous time. A CTBN is a directed (possibly cycli...
BIBE
2008
IEEE
13 years 6 months ago
2008
IEEE
Bayesian network structure learning is a useful tool for elucidation of regulatory structures of biomolecular pathways. The approach however is limited by its acyclicity constraint...
KDD
2010
ACM
13 years 8 months ago
2010
ACM
Feature selection is an important task in order to achieve better generalizability in high dimensional learning, and structure learning of Markov random fields (MRFs) can automat...
ICMCS
2008
IEEE
13 years 11 months ago
2008
IEEE
Several stochastic models provide an effective framework to identify the temporal structure of audiovisual data. Most of them need as input a first video structure, i.e. connecti...
CEC
2009
IEEE
13 years 11 months ago
2009
IEEE
—Structure learning is a crucial component of a multivariate Estimation of Distribution algorithm. It is the part which determines the interactions between variables in the proba...