Approximation Algorithms For Coloring
Approximation Algorithms for Coloring is an algorithmic framework in computational combinatorics that belongs to the class of heuristic methods for NP-hard graph problems and specifically addresses graph coloring by computing near-optimal colorings with provable performance guarantees relative to the chromatic number.
706
Publications
26.4K
Citations
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Authors
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Institutions
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2017–2026
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706
Approximate graph coloring by semidefinite programming
David R. Karger, Rajeev Motwani, Madhu Sudan · Journal of the ACM · 1998 · 429 citations
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University of Illinois Urbana-Champaign, United States
14 publications · 520 citations
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Laboratoire Bordelais de Recherche en Informatique, France
9 publications · 244 citations
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Centre National de la Recherche Scientifique
Paris, France
20 h-index
59 publications
1.8K citations

Tel Aviv University
Tel Aviv, Israel
16 h-index
29 publications
913 citations
University of Illinois Urbana-Champaign
Urbana, United States
16 h-index
28 publications
932 citations
Rutgers, The State University of New Jersey
New Brunswick, United States
15 h-index
20 publications
1.1K citations

Zhejiang Normal University
Jinhua, China
14 h-index
27 publications
665 citations
Sobolev Institute of Mathematics
Novosibirsk, Russia
14 h-index
21 publications
667 citations
Shandong University
Jinan, China
13 h-index
43 publications
1.1K citations
Université de Bordeaux
Bordeaux, France
13 h-index
25 publications
657 citations
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114 publications · 3.6K citations
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46 publications · 2.3K citations
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63 publications · 2.1K citations
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25 publications · 1.1K citations
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