Information Inequalities via Ideas From Additive Combinatorics

Ruzsa’s equivalence theorem provided a framework for converting certain families of inequalities in additive combinatorics to entropic inequalities (which sometimes did not possess stand-alone entropic proofs). In this work, we first establish formal equivalences between some families (different from Ruzsa) of inequalities in additive combinatorics and entropic ones. As a first step to further these equivalences, we establish an information-theoretic characterization of the magnification ratio that could also be of independent interest.

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Publication Details

Journal
IEEE Transactions on Information Theory
Published
2025-04-04
DOI
https://doi.org/10.1109/tit.2025.3557796
Primary Topic
Computability, Logic, AI Algorithms
Type
article
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article

Information Inequalities via Ideas From Additive Combinatorics

Chin Wa Lau, Chandra Nair
IEEE Transactions on Information Theory
Computability, Logic, AI Algorithms
article

Information Inequalities via Ideas From Additive Combinatorics

Chin Wa Lau, Chandra Nair
article en

Abstract

Ruzsa’s equivalence theorem provided a framework for converting certain families of inequalities in additive combinatorics to entropic inequalities (which sometimes did not possess stand-alone entropic proofs). In this work, we first establish formal equivalences between some families (different from Ruzsa) of inequalities in additive combinatorics and entropic ones. As a first step to further these equivalences, we establish an information-theoretic characterization of the magnification ratio that could also be of independent interest.

IEEE Transactions on Information TheoryVol. 71(6)
Chinese University of Hong Kong (HK)
Reduced inequalities
Openalex Percentile: Top 92%
Computability, Logic, AI Algorithms
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