Joint Typicality
Joint Typicality is a probabilistic concept in information theory that characterizes the set of sequence pairs jointly generated by a stationary memoryless source-channel system, distinguished by their empirical entropy converging asymptotically to the true joint entropy of the underlying distribution.
14
Publications
451
Citations
29
Authors
24
Institutions
Publications per year
2017–2026
7
Parents
14
Paul Cuff · IEEE Transactions on Information Theory · 2013 · 238 citations · Full text
A Shannon-Theoretic Approach to the Storage-Retrieval Tradeoff in PIR Systems
On simultaneous min-entropy smoothing
Lukas Drescher, Omar Fawzi · 2013 · 23 citations · Full text
A Joint Typicality Approach to Algebraic Network Information Theory
Sung Hoon Lim, Chen Feng, Adriano Pastore et al. · arXiv (Cornell University) · 2016 · 17 citations · Full text
1–5 of 14
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Korea Institute of Ocean Science and Technology, South Korea
2 publications · 34 citations
2
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1–5 of 29
24

McMaster University
Hamilton, Canada
2 h-index
5 publications
87 citations

University of Amsterdam
Amsterdam, The Netherlands
1 h-index
1 publications
11 citations
Princeton University
Princeton, United States
1 h-index
1 publications
238 citations
University of North Texas at Dallas
Dallas, United States
1 h-index
1 publications
43 citations
Korea Advanced Institute of Science and Technology
Daejeon, South Korea
1 h-index
1 publications
11 citations
Stanford University
Stanford, United States
1 h-index
3 publications
33 citations
New York University
New York, United States
1 h-index
3 publications
33 citations
Japan Advanced Institute of Science and Technology
Nomi Shi, Japan
1 h-index
3 publications
36 citations
1–8 of 24
3 publications · 266 citations
3
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Repository · 2 publications · 34 citations
2
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1 publications · 14 citations
1
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1 publications · 12 citations
1
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1 publications · 11 citations
1
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