An inclusion optimal algorithm for chain graph structure learning: with supplement
2014 (English)In: Proceedings of the 17th International Conference on Arti-cial Intelligence and Statistics, 2014, 778-786 p.Conference paper (Other academic)
This paper presents and proves an extension of Meek’s conjecture to chain graphs under the Lauritzen-Wermuth-Frydenberg interpretation. The proof of the conjecture leads to the development of a structure learning algorithm that finds an inclusion optimal chain graph for any given probability distribution satisfying the composition property. Finally, the new algorithm is experimentally evaluated.
Place, publisher, year, edition, pages
2014. 778-786 p.
, JMLR Workshop and Conference Proceedings, Vol. 33
Chain Graph, Lauritzen-Wermuth-Frydenberg interpretation, Learning
IdentifiersURN: urn:nbn:se:liu:diva-105816OAI: oai:DiVA.org:liu-105816DiVA: diva2:710842
17th International Conference on Artificial Intelligence and Statistics April 22-25, 2014, Reykjavik, Iceland