Efficient Algorithms for Conditional Independence Inference

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dc.contributor.author Bouckaert, Remco en
dc.contributor.author Hemmecke, R en
dc.contributor.author Lindner, S en
dc.contributor.author Studeny, M en
dc.date.accessioned 2012-03-01T20:57:56Z en
dc.date.issued 2010-12 en
dc.identifier.citation Journal of Machine Learning Research 11:3453-3479 Dec 2010 en
dc.identifier.issn 1532-4435 en
dc.identifier.uri http://hdl.handle.net/2292/12519 en
dc.description.abstract 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 (sets of) CI statements into certain integral vectors and to verify by a computer the corresponding algebraic relation between the vectors, called the independence implication. We interpret the previous methods for computer testing of this implication from the point of view of polyhedral geometry. However, the main contribution of the paper is a new method, based on linear programming (LP). The new method overcomes the limitation of former methods to the number of involved variables. We recall/ describe the theoretical basis for all four methods involved in our computational experiments, whose aim was to compare the efficiency of the algorithms. The experiments show that the LP method is clearly the fastest one. As an example of possible application of such algorithms we show that testing inclusion of Bayesian network structures or whether a CI statement is encoded in an acyclic directed graph can be done by the algebraic method. en
dc.language EN en
dc.publisher MICROTOME PUBL en
dc.relation.ispartofseries Journal of Machine Learning Research en
dc.rights Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher. en
dc.rights.uri https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm en
dc.subject conditional independence inference en
dc.subject linear programming approach en
dc.title Efficient Algorithms for Conditional Independence Inference en
dc.type Journal Article en
pubs.begin-page 3453 en
pubs.volume 11 en
dc.rights.holder Copyright: Microtome Publishing ; The Authors en
pubs.author-url http://web.ebscohost.com.ezproxy.auckland.ac.nz/ehost/pdfviewer/pdfviewer?sid=173cca16-1d5d-46e2-905e-d10f237121a7%40sessionmgr15&vid=2&hid=19 en
pubs.end-page 3479 en
dc.rights.accessrights http://purl.org/eprint/accessRights/RestrictedAccess en
pubs.subtype Article en
pubs.elements-id 261148 en
pubs.org-id Science en
pubs.org-id School of Computer Science en
pubs.record-created-at-source-date 2012-02-22 en


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