Variational Predictive Information BottleneckDownload PDF

16 Oct 2019 (modified: 06 Dec 2019)AABI 2019 Symposium Blind SubmissionReaders: Everyone
  • Keywords: Information Bottleneck, Bayesian Inference, Variational Bounds
  • TL;DR: Rederive a wide class of inference procedures from an global information bottleneck objective.
  • Abstract: In classic papers, Zellner (1988, 2002) demonstrated that Bayesian inference could be derived as the solution to an information theoretic functional. Below we derive a generalized form of this functional as a variational lower bound of a predictive information bottleneck objective. This generalized functional encompasses most modern inference procedures and suggests novel ones.
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