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National Repository of Grey Literature 3 records found  Search took 0.00 seconds. 
Credal networks and compositional models: preliminary considerations
 Vejnarová, Jiřina
In the paper we present basic concepts concerning credal networks and compositional models for credal sets and describe the problem of imprecision increase in the first type of these models.
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Multidimensional Probability Distributions: Structure and Learning
 Bína, Vladislav ; Jiroušek, Radim (advisor) ; Vomlelová, Marta (referee) ; Řezanková, Hana (referee)
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.
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Conditioning and Flexibility in Compositional Models
 Kratochvíl, Václav
Reasoning by cases or assumptions is a common form of human reasoning. In case of probability reasoning, this is modeled by conditioning of a multidimensional probability distribution. Compositional models are defined as a multidimensional distributions assembled from a (so called generating) sequence of lowdimensional probability distributions, with the help of operators of composition. In this case, the conditioning process can be viewed as a transformation of one generating sequence into another one. It appears that the conditioning process is simple when conditioning variable appears in the argument of the first distribution of the corresponding generating sequence. That is why we introduce the so called flexible sequences. Flexible sequences are those, which can be reordered in many ways that each variable can appears among arguments of the first distribution. In this paper, we study the problem of flexibility in light of the very recent solution of the equivalence problem.
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