Learning Optimal Bayesian Networks Using A* Search

Changhe Yuan and Brandon Malone and Xiaojian Wu

Abstract

This paper formulates learning optimal Bayesian network as a shortest path finding problem. An A* search algorithm is introduced to solve the problem. With the guidance of a consistent heuristic, the algorithm learns an optimal Bayesian network by only searching the most promising parts of the solution space. Empirical results show that the A* search algorithm significantly improves the time and space efficiency of existing methods on a set of benchmark datasets.

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Bibtex

@INPROCEEDINGS{Yuan11learning,
author = {Changhe Yuan, Brandon Malone, and Xiaojian Wu},
title = {Learning Optimal {B}ayesian Networks Using {A}* Search},
booktitle = {Proceedings of the 22nd International Joint Conference on Artificial Intelligence (IJCAI-11)},
year = {2011},
pages = {2186--2191},
address = {Helsinki, Finland}
}