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Polyhedral aspects of score equivalence in Bayesian network structure learning

SYSNO ASEP	0475315
Document Type	J - Journal Article
R&D Document Type	Journal Article
Subsidiary J	Článek ve WOS
Title	Polyhedral aspects of score equivalence in Bayesian network structure learning
Author(s)	Cussens, J. (GB) Haws, D. (US) Studený, Milan (UTIA-B)_{RID, ORCID}
Number of authors	3
Source Title	Mathematical Programming. - : Springer - ISSN 0025-5610 Roč. 164, 1-2 (2017), s. 285-324
Number of pages	40 s.
Publication form	Print - P
Language	eng - English
Country	NL - Netherlands
Keywords	family-variable polytope ; characteristic-imset polytope ; score equivalent face/facet ; supermodular set function
Subject RIV	BA - General Mathematics
OECD category	Applied mathematics
R&D Projects	GA13-20012S GA ČR - Czech Science Foundation (CSF)
	GA16-12010S GA ČR - Czech Science Foundation (CSF)
Institutional support	UTIA-B - RVO:67985556
UT WOS	000403450600012
EID SCOPUS	84994314193
DOI	10.1007/s10107-016-1087-2
Annotation	This paper deals with faces and facets of the family-variable polytope and the characteristic-imset polytope, which are special polytopes used in integer linear programming approaches to statistically learn Bayesian network structure. A common form of linear objectives to be maximized in this area leads to the concept of score equivalence (SE), both for linear objectives and for faces of the family-variable polytope.
Workplace	Institute of Information Theory and Automation
Contact	Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201.
Year of Publishing	2018

Number of the records: 1