Similarity Learning
Similarity Learning is a machine learning paradigm within content-based recommendation and metric learning that specifically learns a similarity function in vector space retrieval by inducing a distance metric that captures semantic relatedness between items based on their feature representations.
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4.3K
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Publications per year
2017–2026
719
1.5K
Distance Metric Learning with Application to Clustering with Side-Information
Eric P. Xing, Michael I. Jordan, Stuart Russell et al. · 2002 · 2.7K citations
Bo Pang, Lillian Lee · 2005 · 2.2K citations · Full text
From Word Embeddings To Document Distances
Matt J. Kusner, Yu Sun, Nicholas Kolkin et al. · PolyPublie (École Polytechnique de Montréal) · 2015 · 1.5K citations
Re-ranking Person Re-identification with k-Reciprocal Encoding
Zhun Zhong, Liang Zheng, Donglin Cao et al. · 2017 · 1.5K citations · Full text
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Chinese Academy of Sciences
Beijing, China
28 h-index
153 publications
9.6K citations
Microsoft Research Asia (China)
Beijing, China
27 h-index
67 publications
6.8K citations
Tsinghua University
Beijing, China
25 h-index
102 publications
9.9K citations
Microsoft (United States)
Redmond, United States
24 h-index
50 publications
4.4K citations
National University of Singapore
Singapore, Singapore
23 h-index
50 publications
6K citations

University of Electronic Science and Technology of China
Chengdu, China
21 h-index
50 publications
3.1K citations
Nanyang Technological University
Singapore, Singapore
20 h-index
44 publications
2.5K citations
Google (United States)
Mountain View, United States
19 h-index
55 publications
11K citations
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Repository · 81 publications · 4.2K citations
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Conference · 32 publications · 4.6K citations
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30 publications · 1.1K citations
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23 publications · 1.5K citations
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TPAMI · 22 publications · 4.8K citations
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