2020 IEEE International Symposium
on Information Theory

21-26 June 2020 • Los Angeles, California, USA

2020 IEEE International Symposium
on Information Theory

21-26 June 2020 • Los Angeles, California, USA

Technical Program

S.11: Renyi Entropy

Session Type: Lecture
Track: Shannon Theory
Virtual Session: View on Virtual Platform
Session Chair: Ofer Shayevitz, Tel Aviv University
 
S.11.1: Rényi Divergence rates of Ergodic Markov Chains: existence, explicit expressions and properties
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         Valérie Girardin; Laboratoire de Mathématiques Nicolas Oresme
         Philippe Regnault; Laboratoire de Mathématiques de Reims
 
S.11.2: On the Second- and Third-Order Asymptotics of Smooth Rényi Entropy and Their Applications
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         Yuta Sakai; National University of Singapore
         Vincent Y. F. Tan; National University of Singapore
 
S.11.3: Optimum Source Resolvability Rate with Respect to f-Divergences Using the Smooth Renyi Entropy
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         Ryo Nomura; Waseda University
         Hideki Yagi; The University of Electro-Communications
 
S.11.4: On the Rényi Entropy of Log-Concave Sequences
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         James Melbourne; University of Minnesota
         Tomasz Tkocz; Carnegie Mellon University
 
S.11.5: Rényi Bounds on Information Combining
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         Christoph Hirche; University of Copenhagen
 
S.11.6: Explicit Renyi Entropy for Hidden Markov Models
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         Joachim Breitner; University of Pennsylvania
         Maciej Skorski; University of Luxembourg
 

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2021 IEEE International Symposium on Information Theory

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