| Robust multiple kernel k-means using l21-norm L Du, P Zhou, L Shi, H Wang, M Fan, W Wang, YD Shen Twenty-fourth international joint conference on artificial intelligence, 2015 | 236 | 2015 |
| Top-k Feature Selection Framework Using Robust 0–1 Integer Programming X Zhang, M Fan, D Wang, P Zhou, D Tao IEEE Transactions on Neural Networks and Learning Systems 32 (7), 3005-3019, 2020 | 124 | 2020 |
| Self-paced clustering ensemble P Zhou, L Du, X Liu, YD Shen, M Fan, X Li IEEE transactions on neural networks and learning systems 32 (4), 1497-1511, 2020 | 56 | 2020 |
| Learning a robust consensus matrix for clustering ensemble via Kullback-Leibler divergence minimization P Zhou, L Du, H Wang, L Shi, YD Shen Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015 | 50 | 2015 |
| Recovery of corrupted multiple kernels for clustering P Zhou, L Du, L Shi, H Wang, YD Shen Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015 | 47 | 2015 |
| Incremental multi-view spectral clustering P Zhou, YD Shen, L Du, F Ye, X Li Knowledge-Based Systems 174, 73-86, 2019 | 45 | 2019 |
| Unsupervised feature selection for balanced clustering P Zhou, J Chen, M Fan, L Du, YD Shen, X Li Knowledge-Based Systems 193, 105417, 2020 | 44 | 2020 |
| Local and global discriminative learning for unsupervised feature selection L Du, Z Shen, X Li, P Zhou, YD Shen 2013 IEEE 13th International Conference on Data Mining, 131-140, 2013 | 38 | 2013 |
| Unsupervised feature selection with adaptive multiple graph learning P Zhou, L Du, X Li, YD Shen, Y Qian Pattern Recognition 105, 107375, 2020 | 35 | 2020 |
| Clustering ensemble via structured hypergraph learning P Zhou, X Wang, L Du, X Li Information Fusion 78, 171-179, 2022 | 28 | 2022 |
| Self-paced consensus clustering with bipartite graph P Zhou, L Du, X Li Proceedings of the Twenty-Ninth International Conference on International …, 2021 | 24 | 2021 |
| Tri-level robust clustering ensemble with multiple graph learning P Zhou, L Du, YD Shen, X Li Proceedings of the AAAI Conference on Artificial Intelligence 35 (12), 11125 …, 2021 | 19 | 2021 |
| An LLE based heterogeneous metric learning for cross-media retrieval P Zhou, L Du, M Fan, YD Shen Proceedings of the 2015 SIAM international conference on data mining, 64-72, 2015 | 18 | 2015 |
| Unsupervised robust multiple kernel learning via extracting local and global noises P Zhou, F Ye, L Du IEEE Access 7, 34451-34461, 2019 | 12 | 2019 |
| Local graph reconstruction for parameter free unsupervised feature selection L Du, C Ren, X Lv, Y Chen, P Zhou, Z Hu IEEE Access 7, 102921-102930, 2019 | 11 | 2019 |
| Self-paced adaptive bipartite graph learning for consensus clustering P Zhou, X Liu, L Du, X Li ACM Transactions on Knowledge Discovery from Data 17 (5), 1-35, 2023 | 8 | 2023 |
| Convex batch mode active sampling via α-relative pearson divergence H Wang, L Du, P Zhou, L Shi, YD Shen Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015 | 8 | 2015 |
| Incremental multi-view support vector machine P Zhou, YD Shen, L Du, F Ye Proceedings of the 2019 SIAM International Conference on Data Mining, 1-9, 2019 | 7 | 2019 |
| Balanced spectral feature selection P Zhou, J Chen, L Du, X Li IEEE Transactions on Cybernetics, 2022 | 6 | 2022 |
| Experimental design with multiple kernels H Wang, L Du, P Zhou, L Shi, Y Qian, YD Shen 2015 IEEE International Conference on Data Mining, 419-428, 2015 | 5 | 2015 |
Liang Du(杜亮)Associate Professor of Computer Science, Shanxi University在 sxu.edu.cn 的电子邮件经过验证
