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arXiv · 1206.5251

Node Splitting: A Scheme for Generating Upper Bounds in Bayesian Networks

Arthur Choi·Mark Chavira·Adnan Darwiche
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Abstract

We formulate in this paper the mini-bucket algorithm for approximate inference in terms of exact inference on an approximate model produced by splitting nodes in a Bayesian network. The new formulation leads to a number of theoretical and practical implications. First, we show that branchand- bound search algorithms that use minibucket bounds may operate in a drastically reduced search space. Second, we show that the proposed formulation inspires new minibucket heuristics and allows us to analyze existing heuristics from a new perspective. Finally, we show that this new formulation allows mini-bucket approximations to benefit from recent advances in exact inference, allowing one to significantly increase the reach of these approximations.

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Arthur Choi, Mark Chavira, Adnan Darwiche. 2012-06-20. Node Splitting: A Scheme for Generating Upper Bounds in Bayesian Networks. https://arxiv.org/abs/1206.5251

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