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 setting. We study some inferential rules and describe methods and algorithms to compute efficiently the closure of a set of conditional independence statements. (C) 2009 Elsevier Inc. All rights reserved.
Conditional independence structure and its closure: Inferential rules and algorithms / Marco, Baioletti; Busanello, Giuseppe; Vantaggi, Barbara. - In: INTERNATIONAL JOURNAL OF APPROXIMATE REASONING. - ISSN 0888-613X. - STAMPA. - 50:7(2009), pp. 1097-1114. [10.1016/j.ijar.2009.05.002]
Conditional independence structure and its closure: Inferential rules and algorithms
BUSANELLO, GIUSEPPE;VANTAGGI, Barbara
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 setting. We study some inferential rules and describe methods and algorithms to compute efficiently the closure of a set of conditional independence statements. (C) 2009 Elsevier Inc. All rights reserved.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
