Randomized Numerical Linear Algebra is a subfield of numerical computation that employs randomized algorithms to approximate solutions to matrix problems with provable accuracy and efficiency guarantees, distinguishing itself from deterministic methods by leveraging randomness to reduce computational complexity in large-scale linear algebraic tasks.
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131
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84
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2017–2026
41
Publications
71
Petros Drineas, Michael W. Mahoney · Communications of the ACM · 2016 · 239 citations
Randomized Kaczmarz solver for noisy linear systems
BIT Numerical Mathematics · 2010 · 212 citations · Full text
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Authors
131
- MW
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1–5 of 131
Institutions
84
University of California, Berkeley
Berkeley, United States
7 h-index
15 publications
503 citations
University of Chinese Academy of Sciences
Beijing, China
4 h-index
7 publications
387 citations
Academy of Mathematics and Systems Science
Beijing, China
4 h-index
7 publications
387 citations
Chinese Academy of Sciences
Beijing, China
4 h-index
7 publications
387 citations
Rensselaer Polytechnic Institute
Troy, United States
3 h-index
3 publications
373 citations
Cornell University
Ithaca, United States
3 h-index
4 publications
217 citations
Stanford University
Stanford, United States
3 h-index
3 publications
413 citations
Centre National de la Recherche Scientifique
Paris, France
3 h-index
4 publications
79 citations
1–8 of 84
Venues
- arXiv (Cornell University)
Repository · 11 publications · 389 citations
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- Linear Algebra and its Applications
7 publications · 496 citations
7
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- SIAM Journal on Matrix Analysis and Applications
5 publications · 408 citations
5
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- Advances in Computational Mathematics
3 publications · 66 citations
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- Applied Mathematics Letters
3 publications · 49 citations
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