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Distributed cooperative information bottleneck

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Abstract

This paper investigates a scenario where two distant nodes separately observe memoryless process, namely X 1 and X 2 , and can cooperate through multiple exchanges of messages with the goal of enabling a third node to learn “relevant information” (measured in terms of a multi-letter mutual information) about some hidden memoryless process Y, which is arbitrarily dependent on (X 1 , X 2 ). These interactive exchanges yield an explicit cooperation that helps the third node to identify, from the distributed observations X 1 and X 2 , useful features for the inference of Y. An inner and an outer bound to the rate-relevance region of this problem is derived. Optimal characterization of the rate-relevance region under two different conditions on the dependence structures of the involved variables is showed. Also, two examples for Gaussian sources are studied.
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Dates and versions

hal-01742331 , version 1 (24-03-2018)

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Matias Vera, Leonardo Rey Vega, Pablo Piantanida. Distributed cooperative information bottleneck. 2017 IEEE International Symposium on Information Theory (ISIT), Jun 2017, Aachen, Germany. ⟨10.1109/ISIT.2017.8006620⟩. ⟨hal-01742331⟩
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