| Multi-graph fusion for multi-view spectral clustering Z Kang, G Shi, S Huang, W Chen, X Pu, JT Zhou, Z Xu Knowledge-Based Systems 189, 105102, 2020 | 284 | 2020 |
| Auto-weighted multi-view clustering via kernelized graph learning S Huang, Z Kang, IW Tsang, Z Xu Pattern Recognition 88, 174-184, 2019 | 220 | 2019 |
| Auto-weighted multi-view clustering via deep matrix decomposition S Huang, Z Kang, Z Xu Pattern Recognition 97, 107015, 2020 | 189 | 2020 |
| Measuring diversity in graph learning: A unified framework for structured multi-view clustering S Huang, IW Tsang, Z Xu, J Lv IEEE Transactions on Knowledge and Data Engineering 34 (12), 5869-5883, 2021 | 146 | 2021 |
| Robust deep k-means: An effective and simple method for data clustering S Huang, Z Kang, Z Xu, Q Liu Pattern Recognition 117, 107996, 2021 | 131 | 2021 |
| Auto-weighted multi-view co-clustering with bipartite graphs S Huang, Z Xu, IW Tsang, Z Kang Information Sciences 512, 18-30, 2020 | 101 | 2020 |
| Robust multi-view data clustering with multi-view capped-norm k-means S Huang, Y Ren, Z Xu Neurocomputing 311, 197-208, 2018 | 83 | 2018 |
| Self-weighted multi-view clustering with soft capped norm S Huang, Z Kang, Z Xu Knowledge-Based Systems 158, 1-8, 2018 | 79 | 2018 |
| Multiple partitions aligned clustering Z Kang, Z Guo, S Huang, S Wang, W Chen, Y Su, Z Xu The 28th International Joint Conference on Artificial Intelligence (IJCAI …, 2019 | 73 | 2019 |
| Robust graph regularized nonnegative matrix factorization for clustering S Huang, H Wang, T Li, T Li, Z Xu Data Mining and Knowledge Discovery 32, 483-503, 2018 | 65 | 2018 |
| Spectral co-clustering ensemble S Huang, H Wang, D Li, Y Yang, T Li Knowledge-Based Systems 84, 46-55, 2015 | 63 | 2015 |
| Regularized nonnegative matrix factorization with adaptive local structure learning S Huang, Z Xu, Z Kang, Y Ren Neurocomputing 382, 196-209, 2020 | 58 | 2020 |
| Self-paced and auto-weighted multi-view clustering Y Ren, S Huang, P Zhao, M Han, Z Xu Neurocomputing 383, 248-256, 2020 | 57 | 2020 |
| Adaptive local structure learning for document co-clustering S Huang, Z Xu, J Lv Knowledge-Based Systems 148, 74-84, 2018 | 55 | 2018 |
| Model-based evaluation of alternative reactive class closure strategies against COVID-19 QH Liu, J Zhang, C Peng, M Litvinova, S Huang, P Poletti, F Trentini, ... Nature communications 13 (1), 322, 2022 | 42 | 2022 |
| Efficient federated multi-view learning S Huang, W Shi, Z Xu, IW Tsang, J Lv Pattern Recognition 131, 108817, 2022 | 34 | 2022 |
| Self-supervised graph attention networks for deep weighted multi-view clustering Z Huang, Y Ren, X Pu, S Huang, Z Xu, L He Proceedings of the AAAI Conference on Artificial Intelligence 37 (7), 7936-7943, 2023 | 32 | 2023 |
| Nonnegative matrix factorization with adaptive neighbors S Huang, Z Xu, F Wang 2017 International Joint Conference on Neural Networks (IJCNN), 486-493, 2017 | 32 | 2017 |
| Sample-level multi-view graph clustering Y Tan, Y Liu, S Huang, W Feng, J Lv Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 31 | 2023 |
| Partial differential equations meet deep neural networks: A survey S Huang, W Feng, C Tang, J Lv arXiv preprint arXiv:2211.05567, 2022 | 31 | 2022 |
Zenglin XuFudan UniversityVerified email at fudan.edu.cn