377 search results - page 6 / 76 » Learning Bayesian networks from data: An information-theory ... |
ICML
2010
IEEE
13 years 7 months ago
2010
IEEE
Classical dynamic Bayesian networks (DBNs) are based on the homogeneous Markov assumption and cannot deal with heterogeneity and non-stationarity in temporal processes. Various ap...
IJAR
2010
13 years 7 months ago
2010
We recall the basic idea of an algebraic approach to learning Bayesian network (BN) structures, namely to represent every BN structure by a certain (uniquely determined) vector, c...
IJAR
2006
13 years 9 months ago
2006
Probabilistic decision graphs (PDGs) are a representation language for probability distributions based on binary decision diagrams. PDGs can encode (context-specific) independence...
IJAR
2010
13 years 7 months ago
2010
Probabilistic Decision Graphs (PDGs) are a class of graphical models that can naturally encode some context specific independencies that cannot always be efficiently captured by...
JMLR
2010
13 years 3 months ago
2010
We introduce a simple order-based greedy heuristic for learning discriminative structure within generative Bayesian network classifiers. We propose two methods for establishing an...