Randomized Geometric Optimization
Randomized Geometric Optimization is a computational framework within randomized geometric algorithms that employs probabilistic methods to efficiently solve optimization problems involving geometric structures by iteratively refining candidate solutions through random sampling and geometric partitioning.
13
Publications
545
Citations
27
Authors
23
Institutions
Publications per year
2017–2026
1
13
Geometric Applications of a Randomized Optimization Technique
T M Chan · Discrete & Computational Geometry · 1999 · 101 citations · Full text
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23
Duke University
Durham, United States
3 h-index
6 publications
164 citations
New York University
New York, United States
2 h-index
2 publications
104 citations
Ben-Gurion University of the Negev
Beersheba, Israel
2 h-index
4 publications
76 citations
Courant Institute of Mathematical Sciences
New York, United States
2 h-index
2 publications
104 citations

St. Olaf College
Northfield, United States
2 h-index
2 publications
38 citations

Tel Aviv University
Tel Aviv, Israel
2 h-index
2 publications
104 citations
Florida State University
Tallahassee, United States
2 h-index
2 publications
38 citations
Stony Brook University
Stony Brook, United States
2 h-index
2 publications
38 citations
1–8 of 23
2 publications · 189 citations
2
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1 publications · 16 citations
1
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1 publications · 140 citations
1
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IJCGA · 1 publications · 22 citations
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Conference · 1 publications · 12 citations
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1–5