Institute of Information Theory and Automation

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Bibliography

Journal Article

Efficient algorithms for conditional independence inference

Bouckaert R., Hemmecke R., Lindner S., Studený Milan

: Journal of Machine Learning Research vol.11, 1 (2010), p. 3453-3479

: CEZ:AV0Z10750506

: GA201/08/0539, GA ČR, 1M0572, GA MŠk

: conditional independence inference, linear programming approach

: http://library.utia.cas.cz/separaty/2010/MTR/studeny-efficient algorithms for conditional independence inference.pdf

(eng): The topic of the paper is computer testing of (probabilistic) conditional independence (CI) implications by an algebraic method of structural imsets. The basic idea is to transform CI statements into certain integral vectors and to verify by a computer the corresponding algebraic relation between the vectors, called the independence implication. The main contribution of the paper is a new method, based on linear programming (LP), which overcomes the limitation of former methods to the number of involved variables. The computational experiments, described in the paper, also show that the new method is faster than the previous ones.

: BA

2019-01-07 08:39