Derandomization
Derandomization is a theoretical framework in computational complexity that characterizes the systematic reduction or elimination of randomness in algorithms while preserving their correctness and efficiency, distinguishing it from alternative approaches by its focus on converting probabilistic computation into deterministic computation under resource constraints.
175
Publications
7.9K
Citations
279
Authors
135
Institutions
Publications per year
2017–2026
30
175
The discrepancy method: randomness and complexity
Choice Reviews Online · 2002 · 365 citations
Splitters and near-optimal derandomization
Moni Naor, Leonard J. Schulman, A. Srinivasan · 2002 · 306 citations
1–5 of 175
279
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135
Stanford University
Stanford, United States
13 h-index
20 publications
789 citations

Tel Aviv University
Tel Aviv, Israel
11 h-index
14 publications
649 citations
Harvard University
Cambridge, United States
11 h-index
15 publications
955 citations

Weizmann Institute of Science
Rehovot, Israel
11 h-index
14 publications
1K citations
Hebrew University of Jerusalem
Jerusalem, Israel
9 h-index
10 publications
841 citations
Massachusetts Institute of Technology
Cambridge, United States
9 h-index
10 publications
824 citations
University of California San Diego
San Diego, United States
8 h-index
9 publications
793 citations

Institute for Advanced Study
Princeton, United States
6 h-index
7 publications
398 citations
1–8 of 135
12 publications · 521 citations
12
h-index
Repository · 6 publications · 81 citations
6
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CC · 5 publications · 147 citations
5
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3 publications · 721 citations
3
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3 publications · 77 citations
3
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1–5