Completeness Reductions
Completeness Reductions is a type of polynomial-time many-one reduction used in computational complexity theory that establishes the hardness of problems by mapping instances of a known complete problem to instances of a target problem while preserving the membership in a complexity class, thereby demonstrating that the target problem is at least as hard as the hardest problems in that class.
157
Publications
7.8K
Citations
289
Authors
185
Institutions
Publications per year
2017–2026
8
157
Reduction Techniques for Instance-Based Learning Algorithms
D.R. Wilson, Tony Martinez · Machine Learning · 2000 · 1.2K citations · Full text
Node-Deletion Problems on Bipartite Graphs
Mihalis Yannakakis · SIAM Journal on Computing · 1981 · 300 citations
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Institut national de recherche en sciences et technologies du numérique, France
3 publications · 453 citations
3
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Rutgers, The State University of New Jersey, United States
3 publications · 140 citations
3
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3
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185

Cornell University
Ithaca, United States
8 h-index
16 publications
657 citations

Centre National de la Recherche Scientifique
Paris, France
6 h-index
6 publications
185 citations
University of Oxford
Oxford, United Kingdom
5 h-index
7 publications
135 citations
Brown University
Providence, United States
4 h-index
4 publications
470 citations
Boston University
Boston, United States
4 h-index
5 publications
142 citations
Charles University
Prague, Czechia
3 h-index
3 publications
96 citations
Institut national de recherche en sciences et technologies du numérique
Le Chesnay-Rocquencourt, France
3 h-index
3 publications
453 citations

University of Helsinki
Helsinki, Finland
3 h-index
3 publications
453 citations
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13 publications · 718 citations
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8 publications · 468 citations
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5 publications · 116 citations
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4 publications · 60 citations
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4 publications · 121 citations
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