Shared Representation Learning
Shared Representation Learning is a multi-task learning approach that belongs to the category of methods which construct a common latent space across related tasks, distinguished by its mechanism of enforcing parameter sharing or feature alignment to improve generalization through inductive transfer.
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15K
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757
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280
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Publications per year
2017–2026
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MVAE: Multimodal Variational Autoencoder for Fake News Detection
Dhruv Khattar, Jaipal Singh Goud, Manish Gupta et al. · 2019 · 745 citations · Full text
Adversarial Multi-task Learning for Text Classification
Pengfei Liu, Xipeng Qiu, Xuanjing Huang · 2017 · 596 citations · Full text
Cross-Modality Person Re-Identification With Shared-Specific Feature Transfer
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University of Science and Technology of China
Hefei, China
7 h-index
19 publications
2.4K citations
Nanjing University of Science and Technology
Nanjing, China
6 h-index
11 publications
916 citations
Tsinghua University
Beijing, China
6 h-index
14 publications
750 citations

Sun Yat-sen University
Guangzhou, China
6 h-index
11 publications
303 citations

Hong Kong Polytechnic University
Hong Kong, Hong Kong
5 h-index
11 publications
278 citations

Harbin Institute of Technology
Harbin, China
5 h-index
7 publications
287 citations
University College London
London, United Kingdom
5 h-index
13 publications
772 citations

Chinese Academy of Sciences
Beijing, China
5 h-index
13 publications
761 citations
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Repository · 37 publications · 3.2K citations
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TPAMI · 7 publications · 409 citations
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6 publications · 242 citations
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5 publications · 355 citations
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4 publications · 274 citations
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