Graph Transduction
Graph Transduction is a semi-supervised learning method that, within the context of network propagation, leverages both labeled and unlabeled nodes in a graph to infer the labels of unseen nodes by exploiting the graph's structural and feature information.
34
Publications
2.3K
Citations
91
Authors
53
Institutions
Publications per year
2017–2026
12
Variants
Transductive Learning On Graphs
Parents
34
Graph construction and <i>b</i> -matching for semi-supervised learning
Tony Jebara, Jun Wang, Shih‐Fu Chang · 2009 · 325 citations
1–5 of 34
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53
Ca' Foscari University of Venice
Venice, Italy
4 h-index
11 publications
211 citations
Columbia University
New York, United States
4 h-index
11 publications
1.5K citations
Brazilian Society of Computational and Applied Mathematics
São Carlos, Brazil
2 h-index
4 publications
44 citations
University of North Carolina at Chapel Hill
Chapel Hill, United States
2 h-index
12 publications
427 citations
Chongqing Jiaotong University
Chongqing, China
2 h-index
2 publications
79 citations
Temple University
Philadelphia, United States
2 h-index
4 publications
634 citations
Chinese University of Hong Kong
Hong Kong, Hong Kong
2 h-index
4 publications
420 citations

Centre National de la Recherche Scientifique
Paris, France
2 h-index
2 publications
251 citations
1–8 of 53
3 publications · 53 citations
3
h-index
2 publications · 435 citations
2
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Repository · 2 publications · 48 citations
2
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2 publications · 58 citations
2
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TPAMI · 2 publications · 306 citations
2
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1–5