Uncertainty in Artificial Intelligence
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Tightening Fractional Covering Upper Bounds on the Partition Function for High-Order Region Graphs
Tamir Hazan, Jian Peng, Amnon Shashua
Abstract:
In this paper we present a new approach for tightening upper bounds on the partition function. Our upper bounds are based on fractional covering bounds on the entropy function, and result in a concave program to compute these bounds and a convex program to tighten them. To solve these programs effectively for general region graphs we utilize the entropy barrier method, thus decomposing the original programs by their dual programs and solve them with dual block optimization scheme. The entropy barrier method provides an elegant framework to generalize the message-passing scheme to high-order region graph, as well as to solve the block dual steps in closed-form. This is a key for computational relevancy for large problems with thousands of regions.
Keywords:
Pages: 356-366
PS Link:
PDF Link: /papers/12/p356-hazan.pdf
BibTex:
@INPROCEEDINGS{Hazan12,
AUTHOR = "Tamir Hazan and Jian Peng and Amnon Shashua",
TITLE = "Tightening Fractional Covering Upper Bounds on the Partition Function for High-Order Region Graphs",
BOOKTITLE = "Proceedings of the Twenty-Eighth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-12)",
PUBLISHER = "AUAI Press",
ADDRESS = "Corvallis, Oregon",
YEAR = "2012",
PAGES = "356--366"
}


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