In this paper we deal with conditional independence models closed with respect to graphoid properties. Such models come from different uncertainty measures, in particular in a probabilistic coherent setting. We study some inferential rules and describe methods and algorithms to compute efficiently the closure of a set of conditional independence statements.
Conditional independence structure and its closure: inferential rules and algorithms
BAIOLETTI, Marco;
2009
Abstract
In this paper we deal with conditional independence models closed with respect to graphoid properties. Such models come from different uncertainty measures, in particular in a probabilistic coherent setting. We study some inferential rules and describe methods and algorithms to compute efficiently the closure of a set of conditional independence statements.File in questo prodotto:
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