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IJAR
2010
13 years 6 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...
PRICAI
2004
Springer
14 years 29 days ago
2004
Springer
When we have a large amount of information, we usually use categories with a hierarchy, in which all information is assigned. This paper proposes a new method of integrating two ca...
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...
JMLR
2012
11 years 10 months ago
2012
The expectation maximization (EM) algorithm is a popular algorithm for parameter estimation in models with hidden variables. However, the algorithm has several non-trivial limitat...
MICAI
2007
Springer
14 years 1 months ago
2007
Springer
A successful interpretation of data goes through discovering crucial relationships between variables. Such a task can be accomplished by a Bayesian network. The dark side is that, ...