Institute of Information Theory and Automation

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Bibliography

Conference Paper (international conference)

How matroids occur in the context of learning Bayesian network structure

Studený Milan

: Uncertainty in Artificial Intelligence, Proceedings of the Thirty-First Conference (2015), p. 832-841

: 31st Conference on Uncertainty in Artificial Intelligence, (Amsterdam, NL, 12.07.2015-16.07.2015)

: GA13-20012S, GA ČR

: learning Bayesian network structure, matroid, family-variable polytope

: http://library.utia.cas.cz/separaty/2015/MTR/studeny-0447685.pdf

(eng): It is shown 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 globally optimal BN structure learning. The result applies to well-known k-cluster inequalities, which play a crucial role in the ILP approach.

: BA

2019-01-07 08:39