| An overview of recent multi-view clustering L Fu, P Lin, AV Vasilakos, S Wang Neurocomputing 402, 148-161, 2020 | 185 | 2020 |
| Learnable graph convolutional network and feature fusion for multi-view learning Z Chen, L Fu, J Yao, W Guo, C Plant, S Wang Information Fusion 95, 109-119, 2023 | 115 | 2023 |
| Low-rank tensor approximation with local structure for multi-view intrinsic subspace clustering L Fu, J Yang, C Chen, C Zhang Information Sciences 606, 877-891, 2022 | 42 | 2022 |
| Unified low-rank tensor learning and spectral embedding for multi-view subspace clustering L Fu, Z Chen, Y Chen, S Wang IEEE Transactions on Multimedia 25, 4972-4985, 2022 | 42 | 2022 |
| A self-representation method with local similarity preserving for fast multi-view outlier detection Y Wang, C Chen, J Lai, L Fu, Y Zhou, Z Zheng ACM Transactions on Knowledge Discovery from Data 17 (1), 1-20, 2023 | 22 | 2023 |
| Learnable multi-view matrix factorization with graph embedding and flexible loss S Huang, Y Zhang, L Fu, S Wang IEEE Transactions on Multimedia 25, 3259-3272, 2022 | 22 | 2022 |
| Cross-view graph matching for incomplete multi-view clustering JH Yang, LL Fu, C Chen, HN Dai, Z Zheng Neurocomputing 515, 79-88, 2023 | 21 | 2023 |
| Mutual information-driven multi-view clustering L Zhang, L Fu, T Wang, C Chen, C Zhang Proceedings of the 32nd ACM international conference on information and …, 2023 | 13 | 2023 |
| Multi-view learning via low-rank tensor optimization L Fu, Z Chen, S Huang, S Huang, S Wang 2021 IEEE International Conference on Multimedia and Expo (ICME), 1-6, 2021 | 12 | 2021 |
| Multi-view graph convolutional networks with differentiable node selection Z Chen, L Fu, S Xiao, S Wang, C Plant, W Guo ACM Transactions on Knowledge Discovery from Data 18 (1), 1-21, 2023 | 11 | 2023 |
| Multigraph random walk for joint learning of multiview clustering and semisupervised classification S Wang, L Fu, Z Wang, H Xu, W Zhu IEEE Transactions on Computational Social Systems 9 (3), 926-939, 2021 | 9 | 2021 |
| Consistent affinity representation learning with dual low-rank constraints for multi-view subspace clustering L Fu, J Li, C Chen Neurocomputing 514, 113-126, 2022 | 8 | 2022 |
| Subspace-contrastive multi-view clustering L Fu, S Huang, L Zhang, J Yang, Z Zheng, C Zhang, C Chen ACM Transactions on Knowledge Discovery from Data 18 (9), 1-35, 2024 | 7 | 2024 |
| Data-free knowledge distillation via generator-free data generation for Non-IID federated learning S Zhao, T Liao, L Fu, C Chen, J Bian, Z Zheng Neural Networks 179, 106627, 2024 | 6 | 2024 |
| Toward Few-Label Vertical Federated Learning L Zhang, L Fu, C Liu, Z Yang, J Yang, Z Zheng, C Chen ACM Transactions on Knowledge Discovery from Data 18 (7), 1-21, 2024 | 6 | 2024 |
| A structure noise-aware tensor dictionary learning method for high-dimensional data clustering JH Yang, C Chen, HN Dai, LL Fu, Z Zheng Information Sciences 612, 87-106, 2022 | 6 | 2022 |
| Hierarchical representation for multi-view clustering: From intra-sample to intra-view to inter-view JH Yang, C Chen, HN Dai, M Ding, LL Fu, Z Zheng Proceedings of The 31st ACM International Conference on Information …, 2022 | 4 | 2022 |
| Community-aware efficient graph contrastive learning via personalized self-training Y Li, Y Hu, L Fu, C Chen, L Yang, Z Zheng arXiv preprint arXiv:2311.11073, 2023 | 3 | 2023 |
| Multi-view deep matrix factorization with consensual solution from multiple paths S Huang, L Fu, Y Zhang, H Xu, S Wang 2022 IEEE International Conference on Multimedia and Expo (ICME), 1-6, 2022 | 3 | 2022 |
| Hyper-Laplacian Regularized Concept Factorization in Low-Rank Tensor Space for Multi-View Clustering Z Yu, L Fu, Y Chen, Z Cai, G Chao IEEE Transactions on Emerging Topics in Computational Intelligence, 2024 | 2 | 2024 |
Shiping WangFuzhou UniversityZweryfikowany adres z fzu.edu.cn