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Mnoharozměrná pravděpodobnostní rozdělení: Struktura a učení / Multidimensional Probability Distributions: Structure and Learning

The thesis considers a representation of a discrete multidimensional probability distribution using an apparatus of compositional models, and focuses on the theoretical background and structure of search space for structure learning algorithms in the framework of such models and particularly focuses on the subclass of decomposable models. Based on the theoretical results, proposals of basic learning techniques are introduced and compared.

Identiferoai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:72677
Date January 2010
CreatorsBína, Vladislav
ContributorsJiroušek, Radim, Vomlelová, Marta, Řezanková, Hana
PublisherVysoká škola ekonomická v Praze
Source SetsCzech ETDs
LanguageCzech
Detected LanguageEnglish
Typeinfo:eu-repo/semantics/doctoralThesis
Rightsinfo:eu-repo/semantics/restrictedAccess

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