139 search results - page 3 / 28 » Learning Bayesian Network Structure using LP Relaxations |
83
Voted
ICML
2009
IEEE
15 years 10 months ago
2009
IEEE
This paper addresses exact learning of Bayesian network structure from data and expert's knowledge based on score functions that are decomposable. First, it describes useful ...
GECCO
2009
Springer
15 years 2 months ago
2009
Springer
We propose a cooperative-coevolution – Parisian trend – algorithm, IMPEA (Independence Model based Parisian EA), to the problem of Bayesian networks structure estimation. It i...
81
Voted
ICDM
2003
IEEE
15 years 2 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 ...
IJCAI
2001
14 years 11 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
14 years 1 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...