Ranking Loss
Ranking Loss is a type of loss function used in machine learning that penalizes incorrect relative ordering of predicted scores by enforcing a margin between the scores of positive and negative instances in ranking tasks.
289
Publications
23.7K
Citations
988
Authors
293
Institutions
Publications per year
2017–2026
203
Variants
Ranking Losses
Parents
289
Unsupervised Learning of Visual Representations Using Videos
Xiaolong Wang, Abhinav Gupta · 2015 · 967 citations
Simultaneous feature learning and hash coding with deep neural networks
Hanjiang Lai, Yan Pan, Ye Liu et al. · 2015 · 923 citations · Full text
NetVLAD: CNN Architecture for Weakly Supervised Place Recognition
Relja Arandjelović, Petr Gronát, Akihiko Torii et al. · 2016 · 647 citations · Full text
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Chinese Academy of Sciences
Beijing, China
14 h-index
43 publications
2.2K citations
Google (United States)
Mountain View, United States
12 h-index
37 publications
2.6K citations
University of Chinese Academy of Sciences
Beijing, China
12 h-index
42 publications
2.1K citations
Tencent (China)
Shenzhen, China
10 h-index
15 publications
1.4K citations
University of Science and Technology of China
Hefei, China
9 h-index
23 publications
3.1K citations
Nanjing University
Nanjing, China
8 h-index
18 publications
878 citations

Zhejiang University
Hangzhou, China
8 h-index
30 publications
848 citations

Peking University
Beijing, China
7 h-index
18 publications
693 citations
1–8 of 293
Repository · 41 publications · 2.6K citations
24
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Conference · 12 publications · 857 citations
11
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10 publications · 372 citations
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TKDE · 7 publications · 227 citations
7
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6 publications · 302 citations
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