1340 search results - page 5 / 268 » Structure learning of Bayesian networks using constraints |
IJCAI
2001
13 years 8 months ago
2001
The task of causal structure discovery from empirical data is a fundamental problem in many areas. Experimental data is crucial for accomplishing this task. However, experiments a...
ICASSP
2011
IEEE
12 years 10 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...
IJAR
2011
12 years 10 months ago
2011
The basic idea of an algebraic approach to learning Bayesian network (BN) structures is to represent every BN structure by a certain uniquely determined vector, called the standar...
CVPR
2008
IEEE
14 years 8 months ago
2008
IEEE
Graphical models such as Bayesian Networks (BNs) are being increasingly applied to various computer vision problems. One bottleneck in using BN is that learning the BN model param...
UAI
2000
13 years 8 months ago
2000
Algorithms for learning the conditional probabilities of Bayesian networks with hidden variables typically operate within a high-dimensional search space and yield only locally op...