A Sufficiently Fast Algorithm for Finding Close to Optimal Junction Trees
Data Structures and Algorithms
2013-02-18 v1 Artificial Intelligence
Abstract
An algorithm is developed for finding a close to optimal junction tree of a given graph G. The algorithm has a worst case complexity O(c^k n^a) where a and c are constants, n is the number of vertices, and k is the size of the largest clique in a junction tree of G in which this size is minimized. The algorithm guarantees that the logarithm of the size of the state space of the heaviest clique in the junction tree produced is less than a constant factor off the optimal value. When k = O(log n), our algorithm yields a polynomial inference algorithm for Bayesian networks.
Cite
@article{arxiv.1302.3558,
title = {A Sufficiently Fast Algorithm for Finding Close to Optimal Junction Trees},
author = {Ann Becker and Dan Geiger},
journal= {arXiv preprint arXiv:1302.3558},
year = {2013}
}
Comments
Appears in Proceedings of the Twelfth Conference on Uncertainty in Artificial Intelligence (UAI1996)