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Probabilistc Compositional Models: solution of an equivalence problem

SYSNO ASEP	0375138
Document Type	D - Thesis
R&D Document Type	The record was not marked in the RIV
Title	Probabilistc Compositional Models: solution of an equivalence problem
Author(s)	Kratochvíl, Václav (UTIA-B)_{RID, ORCID}
Number of authors	1
Issue data	Praha: Czech Technical University, 2012
Number of pages	118 s.
Publication form	WWW - WWW
Language	eng - English
Country	CZ - Czech Republic
Keywords	compositional model ; probability model ; conditional independence
Subject RIV	BA - General Mathematics
R&D Projects	1M0572 GA MŠMT - Ministry of Education, Youth and Sports (MEYS)
	GA201/09/1891 GA ČR - Czech Science Foundation (CSF)
	GEICC/08/E010 GA ČR - Czech Science Foundation (CSF)
CEZ	AV0Z10750506 - UTIA-B (2005-2011)
Annotation	An integral part of the work with multidimensional probabilistic models, and in particular their learning, is the perfect knowledge of the conditional independence relations of the model. The knowledge of conditional independence relations is understood here as a list of conditional independence relations valid for the model and induced by its structure. However, the representation these relations by such a structure is imperfect - two or more structures may represent the same independence relations - they are equivalent. The equivalence problem can be summed up in the following three questions: (i) how can we recognize whether two structures represent the same set of independence relations; (ii) how can we transform any one structure into another equivalent one in terms of some elementary operations; and (iii) can we generate all structures equivalent with a given one? This thesis presents the complete solution to equivalence problem. We illustrated its usage and, above that, we found a unique representative of a class of equivalent structures.
Workplace	Institute of Information Theory and Automation
Contact	Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201.
Year of Publishing	2012

Number of the records: 1