Maximum Cut Approximation
Maximum Cut Approximation is an algorithmic method in combinatorial optimization that achieves a performance guarantee for the Maximum Cut problem by computing a solution whose cut size approximates the optimal cut within a proven factor.
216
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19.9K
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422
Authors
242
Institutions
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2017–2026
30
Parents
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Optimal Inapproximability Results for MAX‐CUT and Other 2‐Variable CSPs?
Subhash Khot, Guy Kindler, Elchanan Mossel et al. · SIAM Journal on Computing · 2007 · 599 citations · Full text
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Massachusetts Institute of Technology
Cambridge, United States
13 h-index
17 publications
8.9K citations
Carnegie Mellon University
Pittsburgh, United States
11 h-index
13 publications
1.6K citations
University of California, Berkeley
Berkeley, United States
9 h-index
11 publications
1.3K citations

Centre National de la Recherche Scientifique
Paris, France
8 h-index
12 publications
376 citations
Georgia Institute of Technology
Atlanta, United States
7 h-index
9 publications
540 citations
Princeton University
Princeton, United States
7 h-index
11 publications
1.9K citations
IBM Research - Thomas J. Watson Research Center
Yorktown Heights, United States
7 h-index
12 publications
4.3K citations

Tel Aviv University
Tel Aviv, Israel
7 h-index
12 publications
789 citations
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12 publications · 529 citations
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9 publications · 465 citations
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9 publications · 2.1K citations
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Repository · 6 publications · 93 citations
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JACM · 5 publications · 5.1K citations
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