Clustering-based Self-supervision
Clustering-Based Self-Supervision is a self-supervised learning paradigm that belongs to the category of pretext task frameworks, distinguished by its use of unsupervised clustering to generate supervisory signals by assigning pseudo-labels to data instances based on learned feature space groupings.
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453
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Authors
20
Institutions
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2017–2026
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Ministry of Education of the People's Republic of China
Beijing, China
1 h-index
1 publications
19 citations
Duke Kunshan University
Kunshan, China
1 h-index
1 publications
19 citations
State Key Laboratory of Software Development Environment
Beijing, China
1 h-index
7 publications
77 citations

Universidade Estadual de Campinas (UNICAMP)
Campinas, Brazil
1 h-index
1 publications
32 citations
University of California San Diego
San Diego, United States
1 h-index
3 publications
123 citations
Chulalongkorn University
Bangkok, Thailand
1 h-index
2 publications
84 citations
Fano Labs (China)
Hong Kong, China
1 h-index
1 publications
41 citations

University of Windsor
Windsor, Canada
1 h-index
1 publications
15 citations
1–8 of 20
Repository · 2 publications · 82 citations
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Conference · 1 publications · 41 citations
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Repository · 1 publications · 16 citations
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1 publications · 42 citations
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TKDE · 1 publications · 15 citations
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