Average-case Complexity
Average-Case Complexity is a computational complexity measure that characterizes the expected resource consumption of an algorithm over all possible inputs of a given size, under a specified probability distribution, distinguishing it from worst-case and best-case complexity measures by focusing on typical rather than extremal input behavior.
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11.3K
Citations
393
Authors
214
Institutions
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2017–2026
28
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Maximal vector computation in large data sets
Parke Godfrey, J. Ryan Shipley, Jarek Gryz · 2005 · 373 citations
Relations between average case complexity and approximation complexity
Uriel Feige · 2002 · 370 citations
Graph bisection algorithms with good average case behavior
Thanh‐Tung Bui, S.K. Chaudhuri, F. T. Leighton et al. · COMBINATORICA · 1987 · 327 citations
A personal view of average-case complexity
Russell Impagliazzo · 2002 · 298 citations
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Massachusetts Institute of Technology
Cambridge, United States
12 h-index
17 publications
2K citations
Columbia University
New York, United States
11 h-index
16 publications
685 citations
University of California, Berkeley
Berkeley, United States
9 h-index
13 publications
966 citations

University of Warsaw
Warsaw, Poland
8 h-index
9 publications
392 citations
Hebrew University of Jerusalem
Jerusalem, Israel
8 h-index
13 publications
883 citations
University of California, Los Angeles
Los Angeles, United States
7 h-index
9 publications
334 citations
Max Planck Institute for Informatics
Saarbrücken, Germany
7 h-index
7 publications
225 citations
Max Planck Society
Munich, Germany
6 h-index
7 publications
251 citations
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12 publications · 743 citations
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12 publications · 421 citations
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Repository · 11 publications · 506 citations
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4 publications · 58 citations
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4 publications · 123 citations
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