Sublinear-time Optimization
Sublinear-Time Optimization is an algorithmic framework that belongs to the class of optimization methods and is distinguished by its ability to compute approximate solutions to optimization problems in time strictly sublinear in the input size, typically by exploiting sampling, sketching, or local search strategies.
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4.6K
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133
Authors
86
Institutions
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2017–2026
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Approximate Nearest Neighbors: Towards Removing the Curse of Dimensionality
Piotr Indyk · 1998 · 319 citations
A Tight Linear Time (1/2)-Approximation for Unconstrained Submodular Maximization
Niv Buchbinder, Moran Feldman, Joseph Naor et al. · 2012 · 237 citations
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Technion – Israel Institute of Technology
Haifa, Israel
6 h-index
10 publications
764 citations
Google (United States)
Mountain View, United States
4 h-index
5 publications
1.3K citations
University of Michigan
Ann Arbor, United States
3 h-index
7 publications
501 citations
Rutgers, The State University of New Jersey
New Brunswick, United States
3 h-index
3 publications
614 citations
Stanford University
Stanford, United States
3 h-index
3 publications
342 citations
Carnegie Mellon University
Pittsburgh, United States
3 h-index
3 publications
188 citations

Tel Aviv University
Tel Aviv, Israel
3 h-index
7 publications
498 citations
Microsoft (United States)
Redmond, United States
3 h-index
4 publications
404 citations
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4 publications · 469 citations
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2 publications · 71 citations
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Conference · 2 publications · 171 citations
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2 publications · 61 citations
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Repository · 2 publications · 358 citations
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