Probabilistic Analysis
Probabilistic Analysis is a methodological framework within algorithm analysis that characterizes the expected behavior of algorithms under assumptions about the probability distribution of inputs, distinguishing it from worst-case or average-case deterministic analysis by explicitly incorporating randomness in input modeling.
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2017–2026
677
Parents
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V. J. Rayward‐Smith, Thomas H. Cormen, Charles E. Leiserson et al. · Journal of the Operational Research Society · 1991 · 17K citations
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Stanford University
Stanford, United States
34 h-index
100 publications
11.3K citations
University of California, Berkeley
Berkeley, United States
27 h-index
85 publications
13.8K citations
Carnegie Mellon University
Pittsburgh, United States
25 h-index
46 publications
3K citations
Massachusetts Institute of Technology
Cambridge, United States
24 h-index
60 publications
5.6K citations

Centre National de la Recherche Scientifique
Paris, France
22 h-index
87 publications
3.9K citations
Universitat Politècnica de Catalunya
Barcelona, Spain
19 h-index
77 publications
3.8K citations
University of Illinois Urbana-Champaign
Urbana, United States
18 h-index
41 publications
4.5K citations
National University of Singapore
Singapore, Singapore
17 h-index
43 publications
1.6K citations
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33 publications · 1.7K citations
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MDM · 28 publications · 4.4K citations
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26 publications · 2.8K citations
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28 publications · 2.5K citations
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18 publications · 1.2K citations
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