Multi-view Association Learning
Multi-View Association Learning is a computational framework that integrates complementary information from multiple heterogeneous data views to model and infer associations across biological omics layers while preserving the intrinsic structure and modality-specific characteristics of each view.
19
Publications
1.8K
Citations
93
Authors
43
Institutions
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2017–2026
17
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Multi-view learning overview: Recent progress and new challenges
Jing Zhao, Xijiong Xie, Xin Xu et al. · Information Fusion · 2017 · 991 citations
Yunshan Ma, Yingzhi He, An Zhang et al. · Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining · 2022 · 99 citations · Full text
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Shanghai Jiao Tong University
Shanghai, China
2 h-index
4 publications
88 citations

Hunan University
Changsha, China
2 h-index
5 publications
656 citations
Nanjing University of Science and Technology
Nanjing, China
2 h-index
7 publications
144 citations
Kunming University of Science and Technology
Kunming, China
2 h-index
8 publications
226 citations
University of Science and Technology of China
Hefei, China
1 h-index
1 publications
99 citations
Jilin University
Changchun, China
1 h-index
2 publications
198 citations

National University of Defense Technology
Changsha, China
1 h-index
1 publications
991 citations
Boston University
Boston, United States
1 h-index
1 publications
18 citations
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8 publications · 467 citations
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1 publications · 44 citations
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1 publications · 18 citations
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Conference · 1 publications · 99 citations
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CVIU · 1 publications · 46 citations
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