454 search results - page 8 / 91 » Bayesian learning of measurement and structural models |
ICML
1996
IEEE
14 years 8 months ago
1996
IEEE
We introduce a method for learning Bayesian networks that handles the discretization of continuous variables as an integral part of the learning process. The main ingredient in th...
ICML
2006
IEEE
14 years 8 months ago
2006
IEEE
The structure of a Bayesian network (BN) encodes variable independence. Learning the structure of a BN, however, is typically of high computational complexity. In this paper, we e...
IJAR
2010
13 years 6 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...
IJAR
2006
13 years 7 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...
BIBE
2008
IEEE
13 years 9 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...