130 search results - page 4 / 26 » Structure learning of Bayesian networks using a semantic gen... |
ICDM
2003
IEEE
13 years 11 months ago
2003
IEEE
Learning Bayesian network structure from large-scale data sets, without any expertspecified ordering of variables, remains a difficult problem. We propose systematic improvements ...
ICML
2008
IEEE
14 years 6 months ago
2008
IEEE
We propose Laplace max-margin Markov networks (LapM3 N), and a general class of Bayesian M3 N (BM3 N) of which the LapM3 N is a special case with sparse structural bias, for robus...
ECTEL
2006
Springer
13 years 9 months ago
2006
Springer
Bayesian networks are commonly used in cognitive student modeling and assessment. They typically represent the item-concepts relationships, where items are observable responses to ...
ICASSP
2011
IEEE
12 years 9 months ago
2011
IEEE
Recently, the margin criterion has been successfully used for parameter optimization in graphical models. We introduce maximum margin based structure learning for Bayesian network...
ECSQARU
2005
Springer
13 years 11 months ago
2005
Springer
In this paper we explore the use of several types of structural restrictions within algorithms for learning Bayesian networks. These restrictions may codify expert knowledge in a g...