The DOI matches its Crossref record; 158 of the 172 references it cites were found in a registry or an index.
Multi-view learning overview: Recent progress and new challenges
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Integrity signals
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Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Finally, Multiview Learning [417] constructs different views of the object as per the information contained in the different data sources”
From Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI (2020) · cites this paper as [419]
In the citing paper
“Although various ML specialisations such as reinforcement (Coronato et al., 2020), hybrid (Zhou et al., 2019), multi-view (Zhao et al., 2017) and selfsupervised learning (Chen et al., 2019) are now emerging in generic health-care applications, they have not yet gained enough momentum in multi-omics analysis, hence they remain beyond the scope of this review.”
From Using machine learning approaches for multi-omics data analysis: A review (2021) · cites this paper as Zhao et al., 2017
Citations
Cites
Proceedings of IEEE Conference on Computer Vision and Pattern Recognition
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Domain-Adversarial Training of Neural Networks
Ganin, Y., Ustinova, E., Ajakan, H., Germain, P., Larochelle, H., Laviolette, F., Marchand, M., & Lempitsky, V. (2017) · Advances in Computer Vision and Pattern Recognition · doi:10.1007/978-3-319-58347-1_10 · Cited by 8,318
Kernel Methods for Pattern Analysis
Shawe-Taylor, J. S., & Cristianini, N. (2004) · Cambridge University Press eBooks · doi:10.1017/cbo9780511809682 · Cited by 6,610
RELATIONS BETWEEN TWO SETS OF VARIATES
Hotelling, H. (1936) · Biometrika · doi:10.1093/biomet/28.3-4.321 · Cited by 6,041
Proceedings of the 19th International Joint Conference on Artificial Intelligence
Pujol, J. M., Delgado, J., Ramon Sangüesa, A., & Flache, A. (2005) · International Joint Conference on Artificial Intelligence · Cited by 5,771
Combining labeled and unlabeled data with co-training
Blum, A. L., & Mitchell, T. M. (1998) · Conference on Learning Theory · doi:10.1145/279943.279962 · Cited by 5,597
Proceedings European Conference on Computer Vision 2002
Heyden, A., Sparr, G., Nielsen, M., & Johansen, P. (2002) · Lund University Publications (Lund University) · Cited by 5,153
Research works printed but not linked: 3
- Muslea, 2006, Active learning with multiple views, J. Artif. Intell. Res., 27, 203, 10.1613/jair.2005 · DOI
- Sun, 2011, Robust co-training, Int. J. Pattern Recognit. Artif. Intell., 25, 1113, 10.1142/S0218001411008981 · DOI
- Zhu, 2014, Multi-view perceptron: a deep model for learning face identity and view representations, Adv. Neural Inf. Process. Syst., 27, 217
Cited by
Sorted by citations
Barredo Arrieta, A., Díaz-Rodríguez, N., Del Ser, J., Bennetot, A., Tabik, S., Barbado, A., Garcia, S., Gil-Lopez, S., Molina, D., Benjamins, R., et al. (2020) · Information Fusion · doi:10.1016/j.inffus.2019.12.012 · Cited by 10,423
A Comprehensive Survey on Transfer Learning
Zhuang, F., Qi, Z., Duan, K., Xi, D., Zhu, Y., Zhu, H., Xiong, H., & He, Q. (2021) · Proceedings of the IEEE · doi:10.1109/jproc.2020.3004555 · Cited by 6,678
Semi-Supervised Semantic Segmentation With Cross-Consistency Training
Ouali, Y., Hudelot, C., & Tami, M. (2020) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr42600.2020.01269 · Cited by 1,077
GMC: Graph-Based Multi-View Clustering
Wang, H., Yang, Y. Z., & Liu, B. (2019) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2019.2903810 · Cited by 964
Using machine learning approaches for multi-omics data analysis: A review
Reel, P. S., Reel, S., Pearson, E., Trucco, E., & Jefferson, E. (2021) · Biotechnology Advances · doi:10.1016/j.biotechadv.2021.107739 · Cited by 903
Metadata
- Authors
- Zhao, J., Xie, X., Xu, X., & Sun, S.
- Affiliations
- East China Normal University (CN)
- National University of Defense Technology (CN)
- Corresponding author
- Sun, Shiliang
- Venue
- Information Fusion
- Publisher
- Elsevier BV
- Published
- 2017-11
- Volume
- 38
- Pages
- 43-54
- ISSN
- 1566-2535 (ISSN-L)
- OpenAlex
- W2590019597
- Cited by
- 1,002
- References
- 172
- Citations by year
- 2026: 90 · 2025: 104 · 2024: 132 · 2023: 119 · 2022: 125 · 2021: 120 · 2020: 128 · 2019: 98 · 2018: 70 · 2017: 16
- FWCI
- 50.89
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Information Fusion (publishedVersion)
- Funders
- National Natural Science Foundation of China (61673179, 61370175)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Machine Learning and Algorithms
- Physical Sciences › Computer Science › Artificial Intelligence › Domain Adaptation and Few-Shot Learning
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Face and Expression Recognition
- Keywords
- multi-view learning, data fusion, data integration, generalization performance
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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