How Matroids Occur in the Context of Learning Bayesian Network Structure
Abstract
In this paper we show that any connected matroid having a non-trivial cluster of BN variables as its ground set induces a facet-defining inequality for the polytope(s) used in the ILP approach to optimal BN structure learning. Our result applies to well-known k-cluster inequalities, which play a crucial role in the ILP approach.
Cite
Text
Studený. "How Matroids Occur in the Context of Learning Bayesian Network Structure." Conference on Uncertainty in Artificial Intelligence, 2015.Markdown
[Studený. "How Matroids Occur in the Context of Learning Bayesian Network Structure." Conference on Uncertainty in Artificial Intelligence, 2015.](https://mlanthology.org/uai/2015/studeny2015uai-matroids/)BibTeX
@inproceedings{studeny2015uai-matroids,
title = {{How Matroids Occur in the Context of Learning Bayesian Network Structure}},
author = {Studený, Milan},
booktitle = {Conference on Uncertainty in Artificial Intelligence},
year = {2015},
pages = {832-841},
url = {https://mlanthology.org/uai/2015/studeny2015uai-matroids/}
}