Chernoff Bound
Chernoff Bound is a probability inequality that provides exponentially decreasing upper bounds on the tail probabilities of sums of independent random variables, distinguishing itself from other concentration inequalities by its reliance on the moment-generating function to derive tight bounds.
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22.6K
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719
Authors
330
Institutions
Publications per year
2017–2026
46
Variants
Chernoff Inequality
Parents
378
Discriminating States: The Quantum Chernoff Bound
Katrien Audenaert, John Calsamiglia, R. Muñoz-Tapia et al. · Physical Review Letters · 2007 · 533 citations · Full text
A guided tour of chernoff bounds
Torben Hagerup, Christine Rüb · Information Processing Letters · 1990 · 525 citations
The Reduced Nearest Neighbor Rule
Geoffrey W. Gates · 1998 · 419 citations
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330
University of California San Diego
San Diego, United States
11 h-index
21 publications
1.1K citations
University of Illinois Urbana-Champaign
Urbana, United States
10 h-index
17 publications
1.6K citations
Massachusetts Institute of Technology
Cambridge, United States
10 h-index
15 publications
1.7K citations
National University of Singapore
Singapore, Singapore
10 h-index
16 publications
246 citations

Cornell University
Ithaca, United States
9 h-index
12 publications
1K citations

Tohoku University
Sendai, Japan
7 h-index
11 publications
305 citations
Carnegie Mellon University
Pittsburgh, United States
6 h-index
12 publications
741 citations

Centre National de la Recherche Scientifique
Paris, France
5 h-index
6 publications
175 citations
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25 publications · 1.2K citations
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23 publications · 1.4K citations
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Repository · 13 publications · 408 citations
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9 publications · 458 citations
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9 publications · 448 citations
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