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Reconsidering Dependency Networks from an Information Geometry Perspective

By Kazuya Takabatake and Shotaro Akaho
Dependency networks (Heckerman et al., 2000) are potential probabilistic graphical models for systems comprising a large number of variables. Like Bayesian networks, the structure of a dependency network is represented by a directed graph, and each node has a conditional probability table. Learning and inference are realized locally on individual... Show more
July 2, 2021
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Reconsidering Dependency Networks from an Information Geometry Perspective
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