Parameterized Complexity Results for Exact Bayesian Network Structure Learning

Bayesian network structure learning is the notoriously difficult problem of discovering a Bayesian network that optimally represents a given set of training data. In this paper we study the computational worst-case complexity of exact Bayesian network structure learning under graph theoretic restric...

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Vydané v:	arXiv.org
Hlavní autori:	Ordyniak, Sebastian, Szeider, Stefan
Médium:	Paper
Jazyk:	English
Vydavateľské údaje:	Ithaca Cornell University Library, arXiv.org 04.02.2014
Predmet:	Bayesian analysis Complexity Constrictions Evidence Graph theory Machine learning Optimization Polynomials
ISSN:	2331-8422
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