Racing for conditional independence inference

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Abstract

In this article, we consider the computational aspects of deciding whether a conditional independence statement t is implied by a list of conditional independence statements L using the implication related to the method of structural imsets. We present two methods which have the interesting complementary properties that one method performs well to prove that t is implied by L, while the other performs well to prove that t is not implied by L. However, both methods do not perform well the opposite. This gives rise to a parallel algorithm in which both methods race against each other in order to determine effectively whether t is or is not implied. Some empirical evidence is provided that suggest this racing algorithms method performs a lot better than an existing method based on so-called skeletal characterization of the respective implication. Furthermore, the method is able to handle more than five variables. © Springer-Verlag Berlin Heidelberg 2005.

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Bouckaert, R. R., & Studeny, M. (2005). Racing for conditional independence inference. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3571 LNAI, pp. 221–232). Springer Verlag. https://doi.org/10.1007/11518655_20

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