Convex Optimization
Convex Optimization is a subfield of mathematical optimization that studies optimization problems in which the objective function is convex and the feasible set is convex, thereby ensuring that every local optimum is a global optimum and enabling the use of efficient solution methods.
27.8K
Publications
2.1M
Citations
30K
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4.7K
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2017–2026
7.4K
27.8K
Adam: A Method for Stochastic Optimization
Diederik P. Kingma, Jimmy Ba · UvA-DARE (University of Amsterdam) · 2014 · 84.8K citations · Full text
A Simplex Method for Function Minimization
J. A. Nelder, R. Mead · The Computer Journal · 1965 · 28.9K citations
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Stanford University
Stanford, United States
124 h-index
880 publications
231.5K citations
University of California, Berkeley
Berkeley, United States
113 h-index
803 publications
102.9K citations
Princeton University
Princeton, United States
93 h-index
583 publications
82.2K citations
Massachusetts Institute of Technology
Cambridge, United States
90 h-index
689 publications
55.9K citations
Carnegie Mellon University
Pittsburgh, United States
83 h-index
545 publications
62.7K citations

University of Minnesota
Minneapolis, United States
76 h-index
422 publications
43.7K citations

Centre National de la Recherche Scientifique
Paris, France
75 h-index
687 publications
39.6K citations

Cornell University
Ithaca, United States
74 h-index
273 publications
29.4K citations
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1.1K publications · 131.8K citations
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1.1K publications · 119.1K citations
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Repository · 1.8K publications · 87K citations
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533 publications · 54.2K citations
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395 publications · 45.8K citations
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