Original title: LP relaxations and pruning for characteristic imsets
Authors: Studený, Milan
Document type: Research reports
Year: 2012
Language: eng
Series: Research Report, volume: 2323
Abstract: The geometric approach to learning BN structure is to represent it by a certain vector; a suitable such zero-one vector is the characteristic imset, which allows to reformulate the task of finding global maximum of a score over BN structures as an integer linear programming problem. The main contribution of this report is an LP relaxation of the corresponding polytope, that is, a polyhedral description of the domain of the respective integer linear programming problem.
Keywords: integer linear programming; learning Bayesian network structure; quality criterion
Project no.: GA201/08/0539 (CEP)
Funding provider: GA ČR

Institution: Institute of Information Theory and Automation AS ČR (web)
Document availability information: Fulltext is available at external website.
External URL: http://library.utia.cas.cz/separaty/2012/MTR/Studeny-LP relaxations and pruning for characteristic imsets.pdf
Original record: http://hdl.handle.net/11104/0209940

Permalink: http://www.nusl.cz/ntk/nusl-124454


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