Manuscript Topics

Information theory is a rich and broad field that laid the foundations for new mathematical questions and advances of mathematical techniques. Information theory has a significant interplay with probability theory, concentration of measures, statistical inference, combinatorics and graph theory, convex analysis, convex and discrete geometry, and the development of new analytical tools for the derivation of results in linear algebra and group theory. Various information measures appear to be very useful for the derivation of new insightful results in many of these subfields of mathematics.

The aim of this special issue is to present new contributions on the broad mathematical foundations of information theory that can also benefit a large class of problems, and to provide some insight on the interplay between information-theoretic tools and various subfields of mathematics as mentioned above.

Keywords are as follows:  
• Cardinality bounds in convex analysis  
• Chernoff information  
• Converse results with advanced mathematical tools  
• Convex functionals in information theory  
• Concentration of measure inequalities  
• Couplings and Stein’s method in information theory  
• Data-processing inequalities  
• Divergence measures  
• Entropy bounds  
• Entropy rates  
• Expander graphs and error-correcting codes  
• Extremal and additive combinatorics in information theory  
• Estimation of information measures  
• Finite fields and error correcting codes  
• Fisher information  
• Fractional graph theory in information theory  
• Generalized information measures  
• Guessing and task encoding  
• Graph entropy  
• Graph products in information theory  
• I-MMSE  
• Inference statistics  
• Information inequalities with applications  
• Integral representations  
• Kolmogorov complexity  
• Majorization inequalities  
• Mathematical foundations in quantum information theory  
• Method of types and its refinements  
• Performance and complexity bounds  
• Polarization in information theory  
• Ramanujan graphs in coding and information theory  
• Rényi information measures  
• Schur-convexity in information theory  
• Shannon capacity of graphs  
• Shearer’s lemma and applications  
• Smooth entropy  
• Statistical inference  
• Sub and superadditivity  
• Sub and supermodularity  
• Tensorization of information measures  
• Total variation distance  
• Transportation-cost inequalities  
• Wasserstein distance  
• Weight distribution of codes  
• Witsenhausen’s rate  
• Zero-error information theory

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