Smoothed Analysis
Smoothed Analysis is a method for analyzing algorithm performance that considers the expected behavior of an algorithm under small random perturbations of worst-case inputs, thereby interpolating between worst-case and average-case complexity.
108
Publications
7.6K
Citations
264
Authors
150
Institutions
Publications per year
2017–2026
16
Parents
108
Smoothed analysis of algorithms
Daniel A. Spielman, Shang‐Hua Teng · Journal of the ACM · 2004 · 838 citations
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150
University of Bonn
Bonn, Germany
8 h-index
13 publications
273 citations
Massachusetts Institute of Technology
Cambridge, United States
8 h-index
11 publications
1.8K citations
Akamai (United States)
Cambridge, United States
7 h-index
9 publications
1.9K citations

University of Twente
Enschede, The Netherlands
7 h-index
8 publications
278 citations
Stanford University
Stanford, United States
6 h-index
9 publications
393 citations
Microsoft (United States)
Redmond, United States
5 h-index
10 publications
363 citations
Maastricht University
Maastricht, The Netherlands
4 h-index
4 publications
169 citations
Carnegie Mellon University
Pittsburgh, United States
4 h-index
5 publications
230 citations
1–8 of 150
Repository · 10 publications · 366 citations
10
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Repository · 3 publications · 53 citations
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TALG · 3 publications · 50 citations
3
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3 publications · 107 citations
3
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Repository · 3 publications · 104 citations
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