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Racing for Conditional Independence Inference

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Part of the Lecture Notes in Computer Science book series (LNAI,volume 3571)

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.

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Bouckaert, R.R., Studený, M. (2005). Racing for Conditional Independence Inference. In: Godo, L. (eds) Symbolic and Quantitative Approaches to Reasoning with Uncertainty. ECSQARU 2005. Lecture Notes in Computer Science(), vol 3571. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11518655_20

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  • DOI: https://doi.org/10.1007/11518655_20

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-27326-4

  • Online ISBN: 978-3-540-31888-0

  • eBook Packages: Computer ScienceComputer Science (R0)