Established in 2005 under support of MŠMT ČR (project 1M0572)

Publications

Efficient algorithms for conditional independence inference

Typ:
Jornal article
Authors:
Bouckaert R., Hemmecke R., Lindner S., Studený M.
Name of journal:
Journal of Machine Learning Research
Year:
2010
Number:
1 (2010)
Pages:
3453-3479
ISSN:
1532-4435
Keywords:
conditional independence inference, linear programming appro
Anotation:
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.
 
Copyright 2005 DAR XHTML CSS