Convex Conjugates
Convex Conjugates is a fundamental transformation in convex analysis that, given an extended real-valued function, assigns to it its supremum-based dual representation over linear perturbations, thereby generalizing the notion of a dual function in optimization.
27
Publications
2.7K
Citations
43
Authors
29
Institutions
Publications per year
2017–2026
4
Variants
Fenchel ConjugatesFenchel-legendre Transforms
Parents
27
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43
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29
University of California, Santa Barbara
Santa Barbara, United States
2 h-index
5 publications
254 citations

University of Alicante
Alicante, Spain
2 h-index
2 publications
35 citations
University of Washington
Seattle, United States
2 h-index
3 publications
253 citations
University of Virginia
Charlottesville, United States
2 h-index
2 publications
112 citations
Wayne State University
Detroit, United States
1 h-index
1 publications
41 citations
ETH Zurich
Zurich, Switzerland
1 h-index
2 publications
704 citations

Russian New University
Moscow, Russia
1 h-index
1 publications
41 citations
Institute of Biochemistry
Bucharest, Romania
1 h-index
1 publications
61 citations
1–8 of 29
TRAN · 3 publications · 172 citations
3
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2 publications · 35 citations
2
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2 publications · 960 citations
2
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1 publications · 82 citations
1
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1 publications · 38 citations
1
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1–5