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Unifying DAGs and UGs
Linköpings universitet, Institutionen för datavetenskap, Statistik och maskininlärning. Linköpings universitet, Tekniska fakulteten. (STIMA)
2018 (engelsk)Inngår i: Proceedings of the 9th International Conference on Probabilistic Graphical Models (PGM 2018) - Proceedings of Machine Learning Research 72, ML Research Press , 2018, Vol. 72, s. 308-319Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

We introduce a new class of graphical models that generalizes Lauritzen-Wermuth-Frydenbergchain graphs by relaxing the semi-directed acyclity constraint so that only directed cycles are forbidden. Moreover, up to two edges are allowed between any pair of nodes. Specifically, we present local, pairwise and global Markov properties for the new graphical models and prove their equivalence. We also present an equivalent factorization property.

sted, utgiver, år, opplag, sider
ML Research Press , 2018. Vol. 72, s. 308-319
Serie
Proceedings of Machine Learning Research, ISSN 2640-3498 ; 72
Emneord [en]
Directed acyclic graphs, undirected graphs, chain graphs, Markov properties.
HSV kategori
Identifikatorer
URN: urn:nbn:se:liu:diva-159302Scopus ID: 2-s2.0-85075487867OAI: oai:DiVA.org:liu-159302DiVA, id: diva2:1340784
Konferanse
the 9th International Conference on Probabilistic Graphical Models (PGM 2018), Prague, Czech Republic, September 11 - 14, 2018
Tilgjengelig fra: 2019-08-06 Laget: 2019-08-06 Sist oppdatert: 2024-09-01bibliografisk kontrollert

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Peña, Jose M.

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