Label Spreading
Label Spreading is a semi-supervised learning algorithm that belongs to the family of graph-based methods, distinguished by its propagation of label information across data points through a harmonic function on a weighted graph, where the weights reflect pairwise similarities among instances.
28
Publications
1.4K
Citations
90
Authors
48
Institutions
Publications per year
2017–2026
13
Parents
28
Label propagation in video sequences
Vijay Badrinarayanan, Fabio Galasso, Roberto Cipolla · 2010 · 147 citations
1–5 of 28
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Commonwealth Scientific and Industrial Research Organisation, Australia
2 publications · 81 citations
2
h-index
2
h-index
1–5 of 90
48
Universidade de São Paulo
São Paulo, Brazil
3 h-index
6 publications
322 citations

Shanghai Jiao Tong University
Shanghai, China
2 h-index
5 publications
399 citations
Tianjin University of Science and Technology
Tianjin, China
2 h-index
8 publications
172 citations
Brazilian Society of Computational and Applied Mathematics
São Carlos, Brazil
2 h-index
4 publications
78 citations
LinkedIn (United States)
Sunnyvale, United States
1 h-index
2 publications
42 citations
Michigan State University
East Lansing, United States
1 h-index
1 publications
56 citations
Novelis (Canada)
Toronto, Canada
1 h-index
2 publications
30 citations
University of Technology Sydney
Sydney, Australia
1 h-index
2 publications
126 citations
1–8 of 48
2 publications · 43 citations
2
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2 publications · 118 citations
2
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TKDE · 2 publications · 125 citations
2
h-index
1 publications · 71 citations
1
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1 publications · 29 citations
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1–5