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Spotlight
Factor Graph Grammars
David Chiang · Darcey Riley

Thu Dec 10 07:30 AM -- 07:40 AM (PST) @ Orals & Spotlights: Probabilistic Models/Statistics

We propose the use of hyperedge replacement graph grammars for factor graphs, or actor graph grammars (FGGs) for short. FGGs generate sets of factor graphs and can describe a more general class of models than plate notation, dynamic graphical models, case-factor diagrams, and sum-product networks can. Moreover, inference can be done on FGGs without enumerating all the generated factor graphs. For finite variable domains (but possibly infinite sets of graphs), a generalization of variable elimination to FGGs allows exact and tractable inference in many situations. For finite sets of graphs (but possibly infinite variable domains), a FGG can be converted to a single factor graph amenable to standard inference techniques.

Author Information

David Chiang (University of Notre Dame)
Darcey Riley (University of Notre Dame)

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