Approximating the Partition Function by Deleting and then Correcting for Model Edges
Arthur Choi, Adnan Darwiche
We propose an approach for approximating the partition function which is based on two steps: (1) computing the partition function of a simplified model which is obtained by deleting model edges, and (2) rectifying the result by applying an edge-by-edge correction. The approach leads to an intuitive framework in which one can trade-off the quality of an approximation with the complexity of computing it. It also includes the Bethe free energy approximation as a degenerate case. We develop the approach theoretically in this paper and provide a number of empirical results that reveal its practical utility.
PDF Link: /papers/08/p79-choi.pdf
AUTHOR = "Arthur Choi
and Adnan Darwiche",
TITLE = "Approximating the Partition Function by Deleting and then Correcting for Model Edges",
BOOKTITLE = "Proceedings of the Twenty-Fourth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-08)",
PUBLISHER = "AUAI Press",
ADDRESS = "Corvallis, Oregon",
YEAR = "2008",
PAGES = "79--87"