Integer Linear Programming for the Bayesian network structure learning problem

Bayesian networks are a commonly used method of representing conditional probability relationships between a set of variables in the form of a directed acyclic graph (DAG). Determination of the DAG which best explains observed data is an NP-hard problem [1]. This problem can be stated as a constrain...

Full description

Saved in:

Bibliographic Details
Published in:	Artificial intelligence Vol. 244; pp. 258 - 271
Main Authors:	Bartlett, Mark, Cussens, James
Format:	Journal Article
Language:	English
Published:	Amsterdam Elsevier B.V 01.03.2017 Elsevier Science Ltd
Subjects:	Bayesian analysis Bayesian networks Conditional probability Constrained optimisation Cutting planes Economic models Integer Linear Programming Integer programming Linear programming Machine learning Separation Constrained optimisation Separation Bayesian networks Cutting planes Integer Linear Programming
ISSN:	0004-3702, 1872-7921
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!