6533b86efe1ef96bd12ccb3d
RESEARCH PRODUCT
Marginalizing in Undirected Graph and Hypergraph Models
Enrique F. CastilloJuan FerrándizPilar Sanmartinsubject
FOS: Computer and information sciencesArtificial Intelligence (cs.AI)Computer Science - Artificial IntelligenceComputer Science::Discrete Mathematicsdescription
Given an undirected graph G or hypergraph X model for a given set of variables V, we introduce two marginalization operators for obtaining the undirected graph GA or hypergraph HA associated with a given subset A c V such that the marginal distribution of A factorizes according to GA or HA, respectively. Finally, we illustrate the method by its application to some practical examples. With them we show that hypergraph models allow defining a finer factorization or performing a more precise conditional independence analysis than undirected graph models.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2013-01-30 |