Parallel Selection Algorithms
Parallel Selection Algorithms is a computational method within parallel complexity theory that identifies the k-th smallest element in an unordered dataset by concurrently executing selection and comparison operations across multiple processors to reduce time complexity relative to sequential approaches.
75
Publications
3.6K
Citations
218
Authors
108
Institutions
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2017–2026
18
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Computing with Noisy Information
Uriel Feige, Prabhakar Raghavan, David Peleg et al. · SIAM Journal on Computing · 1994 · 314 citations
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Hong Kong University of Science and Technology, Hong Kong SAR China
4 publications · 189 citations
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Second Affiliated Hospital of Chengdu University of Traditional Chinese, China
3 publications · 78 citations
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Stanford University
Stanford, United States
4 h-index
4 publications
721 citations
Northwestern University
Evanston, United States
4 h-index
6 publications
185 citations
Fudan University
Shanghai, China
3 h-index
3 publications
78 citations
IBM (United States)
Armonk, United States
3 h-index
3 publications
86 citations
Purdue University West Lafayette
West Lafayette, United States
3 h-index
3 publications
40 citations

University of Electronic Science and Technology of China
Chengdu, China
3 h-index
3 publications
78 citations

Centre National de la Recherche Scientifique
Paris, France
2 h-index
2 publications
35 citations
Franche-Comté Électronique Mécanique Thermique et Optique - Sciences et Technologies
Besançon, France
2 h-index
2 publications
35 citations
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3 publications · 166 citations
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2 publications · 44 citations
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2 publications · 437 citations
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2 publications · 40 citations
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2 publications · 73 citations
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