Computational Convexity
Computational Convexity is a systematic framework within convex geometry that integrates algorithmic methods and computational techniques to analyze, construct, and optimize convex sets, functions, and related structures, distinguished by its focus on the effective implementation and complexity of geometric reasoning in discrete and continuous domains.
77
Publications
3.7K
Citations
160
Authors
120
Institutions
Publications per year
2017–2026
4
Parents
77
1–5 of 77
160
3
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1–5 of 160
120

Centre National de la Recherche Scientifique
Paris, France
4 h-index
5 publications
261 citations
California Institute of Technology
Pasadena, United States
3 h-index
3 publications
304 citations
Carnegie Mellon University
Pittsburgh, United States
3 h-index
6 publications
131 citations
University of Michigan
Ann Arbor, United States
2 h-index
4 publications
250 citations
University of California, Berkeley
Berkeley, United States
2 h-index
2 publications
259 citations
Princeton University
Princeton, United States
2 h-index
5 publications
83 citations
Georgia Institute of Technology
Atlanta, United States
2 h-index
3 publications
53 citations
University of Iowa
Iowa City, United States
2 h-index
2 publications
34 citations
1–8 of 120
9 publications · 427 citations
9
h-index
3 publications · 138 citations
3
h-index
2 publications · 191 citations
2
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PROC · 2 publications · 23 citations
2
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2 publications · 25 citations
2
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1–5