About: Integer linear programming approach to learning Bayesian network structure: towards the essential graph

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rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
Description	The basic idea of a geometric approach to learning a Bayesian network (BN) structure is to represent every BN structure by a certain vector. This may allow one to re-formulate the task of finding the global maximum of a score over BN structures as an integer linear programming (ILP) problem. Suitable such a zero-one vector representative is the characteristic imset, introduced in 2010. In this paper, extensions of characteristic imsets are considered which additionally encode chain graphs without flags equivalent to acyclic directed graphs. The main contribution is the polyhedral description of the respective domain of the ILP problem. The advantage of this approach is that, as a by-product of the ILP optimization procedure, one may get the essential graph, which is a traditional graphical BN representative. The basic idea of a geometric approach to learning a Bayesian network (BN) structure is to represent every BN structure by a certain vector. This may allow one to re-formulate the task of finding the global maximum of a score over BN structures as an integer linear programming (ILP) problem. Suitable such a zero-one vector representative is the characteristic imset, introduced in 2010. In this paper, extensions of characteristic imsets are considered which additionally encode chain graphs without flags equivalent to acyclic directed graphs. The main contribution is the polyhedral description of the respective domain of the ILP problem. The advantage of this approach is that, as a by-product of the ILP optimization procedure, one may get the essential graph, which is a traditional graphical BN representative. (en)
Title	Integer linear programming approach to learning Bayesian network structure: towards the essential graph Integer linear programming approach to learning Bayesian network structure: towards the essential graph (en)
skos:prefLabel	Integer linear programming approach to learning Bayesian network structure: towards the essential graph Integer linear programming approach to learning Bayesian network structure: towards the essential graph (en)
skos:notation	RIV/67985556:_____/12:00381536!RIV13-AV0-67985556
http://linked.open...avai/riv/aktivita	I P
http://linked.open...avai/riv/aktivity	I, P(GA201/08/0539)
http://linked.open...vai/riv/dodaniDat	2013
http://linked.open...aciTvurceVysledku	Studený, Milan
http://linked.open.../riv/druhVysledku	D - Článek ve sborníku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	Ústav teorie informace a automatizace AV ČR, v. v. i.
http://linked.open...dnocenehoVysledku	142077
http://linked.open...ai/riv/idVysledku	RIV/67985556:_____/12:00381536
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	learning Bayesian network structure; characteristic imset; essential graph (en)
http://linked.open.../riv/klicoveSlovo	characteristic imset essential graph learning Bayesian network structure
http://linked.open...ontrolniKodProRIV	[079358100E57]
http://linked.open...v/mistoKonaniAkce	Granada
http://linked.open...i/riv/mistoVydani	Granada
http://linked.open...i/riv/nazevZdroje	Proceedings of the 6th European Workshop on Graphical Models
http://linked.open...in/vavai/riv/obor	BA
http://linked.open...ichTvurcuVysledku	1 (xsd:int)
http://linked.open...cetTvurcuVysledku	1 (xsd:int)
http://linked.open...vavai/riv/projekt	Conditional independence structures: graphical and algebraic approaches
http://linked.open...UplatneniVysledku	2012
http://linked.open...iv/tvurceVysledku	Studený, Milan
http://linked.open...vavai/riv/typAkce	EUR - Evropská
http://linked.open.../riv/zahajeniAkce	2012-09-19 (xsd:date)
number of pages	8 (xsd:int)
http://purl.org/ne...btex#hasPublisher	DESCAI, University of Granada
https://schema.org/isbn	978-84-15536-57-4

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