ML Anthology

Learning Optimal Bayesian Networks Using A* Search

Changhe Yuan, Brandon M. Malone, XiaoJian Wu
IJCAI 2011 pp. 2186-2191
doi:10.5591/978-1-57735-516-8/IJCAI11-364 /ijcai/2011/yuan2011ijcai-learning/

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 networkby 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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Cite

Text

Yuan et al. "Learning Optimal Bayesian Networks Using A* Search." International Joint Conference on Artificial Intelligence, 2011. doi:10.5591/978-1-57735-516-8/IJCAI11-364

Markdown

[Yuan et al. "Learning Optimal Bayesian Networks Using A* Search." International Joint Conference on Artificial Intelligence, 2011.](https://mlanthology.org/ijcai/2011/yuan2011ijcai-learning/) doi:10.5591/978-1-57735-516-8/IJCAI11-364

BibTeX

@inproceedings{yuan2011ijcai-learning,
  title     = {{Learning Optimal Bayesian Networks Using A* Search}},
  author    = {Yuan, Changhe and Malone, Brandon M. and Wu, XiaoJian},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {2011},
  pages     = {2186-2191},
  doi       = {10.5591/978-1-57735-516-8/IJCAI11-364},
  url       = {https://mlanthology.org/ijcai/2011/yuan2011ijcai-learning/}
}