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arXiv · 1301.2256

Pre-processing for Triangulation of Probabilistic Networks

Hans L. Bodlaender·Arie M. C. A. Koster·Frank van den Eijkhof·Linda C. van der Gaag
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Abstract

The currently most efficient algorithm for inference with a probabilistic network builds upon a triangulation of a network's graph. In this paper, we show that pre-processing can help in finding good triangulations forprobabilistic networks, that is, triangulations with a minimal maximum clique size. We provide a set of rules for stepwise reducing a graph, without losing optimality. This reduction allows us to solve the triangulation problem on a smaller graph. From the smaller graph's triangulation, a triangulation of the original graph is obtained by reversing the reduction steps. Our experimental results show that the graphs of some well-known real-life probabilistic networks can be triangulated optimally just by preprocessing; for other networks, huge reductions in their graph's size are obtained.

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Hans L. Bodlaender, Arie M. C. A. Koster, Frank van den Eijkhof, Linda C. van der Gaag. 2013-01-10. Pre-processing for Triangulation of Probabilistic Networks. https://arxiv.org/abs/1301.2256

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