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Multi-view learning overview: Recent progress and new challenges
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“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
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Zhao, J., & Sun, S. (2014) · Lecture notes in computer science · doi:10.1007/978-3-319-11812-3_30 · Cited by 29
Self-citationSynthesis of maximum margin and multiview learning using unlabeled data
Szedmák, S., & Shawe-Taylor, J. S. (2006) · Neurocomputing · doi:10.1016/j.neucom.2006.11.012 · Cited by 28
Multi-view Transfer Learning with Adaboost
Xu, Z., & Sun, S. (2011) · Proceedings - International Conference on Tools with Artificial Intelligence, TAI · doi:10.1109/ictai.2011.65 · Cited by 27
Self-citationKumar, V., & Minz, S. (2015) · International Symposium on Women in Computing and Informatics · doi:10.1145/2791405.2791443 · Cited by 27
Information-Theoretic Multi-view Domain Adaptation: A Theoretical and Empirical Study
Yang, P., & Gao, W. (2014) · Journal of Artificial Intelligence Research · doi:10.1613/jair.4190 · Cited by 24
Multi-view Ensemble Learning for Poem Data Classification Using SentiWordNet
Kumar, V., & Minz, S. (2014) · Smart innovation, systems and technologies · doi:10.1007/978-3-319-07353-8_8 · Cited by 22
Active learning of Gaussian processes with manifold-preserving graph reduction
Zhou, J., & Sun, S. (2014) · Neural Computing and Applications · doi:10.1007/s00521-014-1643-8 · Cited by 20
Self-citationMakihara, Y., Mansur, A., Muramatsu, D., Uddin, M. Z., & Yagi, Y. (2015) · International Conference on Automatic Face and Gesture Recognition · doi:10.1109/fg.2015.7163131 · Cited by 19
Variational dependent multi-output Gaussian process dynamical systems
ZhaoJing, Z., & SunShiliang (2016) · Journal of Machine Learning Research · doi:10.5555/2946645.3007074 · Cited by 18
Gaussian process versus margin sampling active learning
Zhou, J., & Sun, S. (2015) · Neurocomputing · doi:10.1016/j.neucom.2015.04.086 · Cited by 17
Self-citationMultiview clustering : a late fusion approach using latent models
Bruno, É., & Marchand‐Maillet, S. (2009) · Archive ouverte UNIGE (University of Geneva) · Cited by 16
Zhu, Y., Gao, W., & Zhou, Z. (2015) · Cited by 13
Large-margin multi-view Gaussian process
Xu, C., Tao, D., Li, Y., & Xu, C. (2014) · Multimedia Systems · doi:10.1007/s00530-014-0389-6 · Cited by 11
Bayesian Multiview Dimensionality Reduction for Learning Predictive Subspaces
Gönen, M., Bozkurt, G. G., & Fikret, G. (2014) · Frontiers in artificial intelligence and applications · doi:10.3233/978-1-61499-419-0-387 · Cited by 10
Collaborative Multi-View Denoising
Zhang, L., Wang, S., Zhang, X., Wang, Y., Li, B., Shen, D. G., & Ji, S. (2016) · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · doi:10.1145/2939672.2939811 · Cited by 9
Beyond CCA: Moment Matching for Multi-View ModelsPreprint
Podosinnikova, A., Bach, F., & Lacoste-Julien, S. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1602.09013 · Cited by 8
Multiview cluster ensembles for multimodal MRI segmentation
Méndez, C. A., Summers, P. E., & Menegaz, G. (2015) · International Journal of Imaging Systems and Technology · doi:10.1002/ima.22121 · Cited by 6
Revisiting Gaussian process dynamical models
Zhao, J., & Sun, S. (2015) · International Conference on Artificial Intelligence · Cited by 4
Self-citation
Flagged first, then by citations
14 of the 172 references couldn’t be matched to a known paper.
Research works printed but not linked: 3
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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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