Randomized Algorithms
Randomized Algorithms is an algorithmic design paradigm in which algorithms deliberately employ internal random choices during their execution, so that key performance measures such as running time or output correctness become random variables over these choices rather than being uniquely determined by the input alone.
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2017–2026
214
Variants
Probabilistic Algorithms
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
Greedy Randomized Adaptive Search Procedures
Thomas A. Feo, Maurício G. C. Resende · Journal of Global Optimization · 1995 · 2.7K citations
How to construct random functions
Oded Goldreich, Shafi Goldwasser, Silvio Micali · Journal of the ACM · 1986 · 2.1K citations · Full text
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University of California, Berkeley
Berkeley, United States
31 h-index
63 publications
11.5K citations
Carnegie Mellon University
Pittsburgh, United States
30 h-index
67 publications
6.1K citations
Massachusetts Institute of Technology
Cambridge, United States
29 h-index
75 publications
11.1K citations
Stanford University
Stanford, United States
28 h-index
61 publications
4.3K citations
Hebrew University of Jerusalem
Jerusalem, Israel
25 h-index
46 publications
4.8K citations

Tel Aviv University
Tel Aviv, Israel
24 h-index
58 publications
3.7K citations

Centre National de la Recherche Scientifique
Paris, France
23 h-index
65 publications
2.9K citations
Technion – Israel Institute of Technology
Haifa, Israel
22 h-index
43 publications
2.7K citations
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44 publications · 3.6K citations
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38 publications · 2.3K citations
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Repository · 58 publications · 1.6K citations
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JACM · 25 publications · 4.7K citations
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