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Efficient algorithms for conditional independence inference

SYSNO ASEP	0353652
Document Type	J - Journal Article
R&D Document Type	Journal Article
Subsidiary J	Článek ve WOS
Title	Efficient algorithms for conditional independence inference
Author(s)	Bouckaert, R. (NZ) Hemmecke, R. (DE) Lindner, S. (DE) Studený, Milan (UTIA-B)_{RID, ORCID}
Source Title	Journal of Machine Learning Research - ISSN 1532-4435 Roč. 11, č. 1 (2010), s. 3453-3479
Number of pages	27 s.
Language	eng - English
Country	US - United States
Keywords	conditional independence inference ; linear programming approach
Subject RIV	BA - General Mathematics
R&D Projects	GA201/08/0539 GA ČR - Czech Science Foundation (CSF)
	1M0572 GA MŠMT - Ministry of Education, Youth and Sports (MEYS)
CEZ	AV0Z10750506 - UTIA-B (2005-2011)
UT WOS	000286637200006
Annotation	The topic of the paper is computer testing of (probabilistic) conditional independence (CI) implications by an algebraic method of structural imsets. The basic idea is to transform CI statements into certain integral vectors and to verify by a computer the corresponding algebraic relation between the vectors, called the independence implication. The main contribution of the paper is a new method, based on linear programming (LP), which overcomes the limitation of former methods to the number of involved variables. The computational experiments, described in the paper, also show that the new method is faster than the previous ones.
Workplace	Institute of Information Theory and Automation
Contact	Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201.
Year of Publishing	2011

Number of the records: 1