BEEM : Bucket Elimination with External Memory
Artificial Intelligence
2012-03-19 v1 Data Structures and Algorithms
Abstract
A major limitation of exact inference algorithms for probabilistic graphical models is their extensive memory usage, which often puts real-world problems out of their reach. In this paper we show how we can extend inference algorithms, particularly Bucket Elimination, a special case of cluster (join) tree decomposition, to utilize disk memory. We provide the underlying ideas and show promising empirical results of exactly solving large problems not solvable before.
Cite
@article{arxiv.1203.3487,
title = {BEEM : Bucket Elimination with External Memory},
author = {Kalev Kask and Rina Dechter and Andrew E. Gelfand},
journal= {arXiv preprint arXiv:1203.3487},
year = {2012}
}
Comments
Appears in Proceedings of the Twenty-Sixth Conference on Uncertainty in Artificial Intelligence (UAI2010)