Structural-EM for Learning PDG Models from Incomplete Data
Probabilistic Decision Graphs (PDGs) are a class of graphical models that can naturally encode some context specific independencies that cannot always be efficiently captured by other popular models, such as Bayesian Networks. Furthermore, inference can be carried out efficiently over a PDG, in time...
| Główni autorzy: | , , |
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| Format: | info:eu-repo/semantics/report |
| Język: | English |
| Wydane: |
2012
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| Dostęp online: | http://hdl.handle.net/10835/1551 |