Large-scale Convex Optimization
Large-Scale Convex Optimization is a subfield of mathematical optimization that focuses on the theory and algorithms for solving convex optimization problems involving a large number of variables or constraints, where scalability and computational efficiency are central challenges.
1.1K
Publications
79.1K
Citations
2.2K
Authors
839
Institutions
Publications per year
2017–2026
383
Parents
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1–5 of 1.1K
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839
University of California, Berkeley
Berkeley, United States
25 h-index
77 publications
3.8K citations
Stanford University
Stanford, United States
23 h-index
88 publications
8.3K citations
Carnegie Mellon University
Pittsburgh, United States
19 h-index
41 publications
3.1K citations
Massachusetts Institute of Technology
Cambridge, United States
18 h-index
50 publications
2K citations
Georgia Institute of Technology
Atlanta, United States
18 h-index
34 publications
3K citations
Princeton University
Princeton, United States
18 h-index
33 publications
2.5K citations

Sapienza University of Rome
Rome, Italy
17 h-index
32 publications
1.3K citations

University of Minnesota
Minneapolis, United States
16 h-index
33 publications
2.4K citations
1–8 of 839
72 publications · 7.4K citations
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Repository · 146 publications · 5.7K citations
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55 publications · 6.9K citations
36
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44 publications · 2.7K citations
25
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26 publications · 1.3K citations
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