Subadditivity Beyond Trees and the Chi-Squared Mutual Information

Emmanuel Abbe, Enric Boix Adserà

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Evans et al. [1] proved the subadditivity of the mutual information in the broadcasting on tree model with binary vertex labels and symmetric edge channels. They raised the question of whether such subadditivity extends to loopy graphs in some appropriate way. We propose here such a generalization for general graphs and binary vertex labels. With enough channel symmetry, the generalization applies to arbitrary graphs, and with partial symmetry, it applies to series-parallel graphs. The results are obtained using the Chi-squared mutual information rather than the classical KL-mutual information (for which some of our bounds do not hold). Various properties of the Chi-squared mutual information are discussed.

Original languageEnglish (US)
Title of host publication2019 IEEE International Symposium on Information Theory, ISIT 2019 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages697-701
Number of pages5
ISBN (Electronic)9781538692912
DOIs
StatePublished - Jul 2019
Externally publishedYes
Event2019 IEEE International Symposium on Information Theory, ISIT 2019 - Paris, France
Duration: Jul 7 2019Jul 12 2019

Publication series

NameIEEE International Symposium on Information Theory - Proceedings
Volume2019-July
ISSN (Print)2157-8095

Conference

Conference2019 IEEE International Symposium on Information Theory, ISIT 2019
CountryFrance
CityParis
Period7/7/197/12/19

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Information Systems
  • Modeling and Simulation
  • Applied Mathematics

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