Structured Support Vector Machines
Structured Support Vector Machines is a discriminative machine learning model that extends the standard support vector machine framework to structured output spaces by jointly learning a scoring function over input-output pairs and optimizing prediction under a structured loss function.
103
Publications
5.1K
Citations
276
Authors
131
Institutions
Publications per year
2017–2026
22
Parents
103
A survey of kernels for structured data
Thomas Gärtner · ACM SIGKDD Explorations Newsletter · 2003 · 450 citations
1–5 of 103
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Institute of Science and Technology Austria, Austria
3 publications · 80 citations
3
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3
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3
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1–5 of 276
131
Toyota Technological Institute at Chicago
Chicago, United States
5 h-index
13 publications
373 citations
CentraleSupélec
Gif-sur-Yvette, France
5 h-index
7 publications
151 citations
University of Oxford
Oxford, United Kingdom
5 h-index
7 publications
187 citations

City University of Hong Kong
Hong Kong, Hong Kong
4 h-index
11 publications
988 citations
Microsoft (United States)
Redmond, United States
4 h-index
10 publications
510 citations

The University of Adelaide
Adelaide, Australia
4 h-index
8 publications
217 citations
ETH Zurich
Zurich, Switzerland
3 h-index
5 publications
198 citations
University of Cambridge
Cambridge, United Kingdom
3 h-index
7 publications
224 citations
1–8 of 131
Repository · 8 publications · 207 citations
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TPAMI · 4 publications · 223 citations
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4 publications · 175 citations
4
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3 publications · 51 citations
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2 publications · 47 citations
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