| Robust Graph Learning from Noisy Data Z Kang, H Pan, SCH Hoi, Z Xu IEEE Transactions on Cybernetics 50 (5), 1833-1843, 2020 | 224 | 2020 |
| Large-scale Multi-view Subspace Clustering in Linear Time Z Kang, W Zhou, Z Zhao, J Shao, M Han, Z Xu Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI 2020) 34 (04 …, 2020 | 156 | 2020 |
| Partition Level Multiview Subspace Clustering Z Kang, X Zhao, C Peng, H Zhu, JT Zhou, X Peng, W Chen, Z Xu Neural Networks 122, 279-288, 2020 | 150 | 2020 |
| 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, 2019 | 147 | 2019 |
| Robust PCA via Nonconvex Rank Approximation Z Kang, C Peng, Q Cheng The IEEE International Conference on Data Mining (ICDM 2015), 2015 | 147 | 2015 |
| Auto-weighted multi-view clustering via kernelized graph learning S Huang, Z Kang, IW Tsang, Z Xu Pattern Recognition 88, 174-184, 2019 | 146 | 2019 |
| Low-rank Kernel Learning for Graph-based Clustering Z Kang, L Wen, W Chen, Z Xu Knowledge-Based Systems 163, 510-517, 2019 | 140 | 2019 |
| Auto-weighted multi-view clustering via deep matrix decomposition S Huang, Z Kang, Z Xu Pattern Recognition 97, 107015, 2020 | 116 | 2020 |
| Top-N Recommender System via Matrix Completion Z Kang, C Peng, Q Cheng Thirtieth AAAI Conference on Artificial Intelligence(AAAI-16), 2016 | 113 | 2016 |
| Kernel-driven Similarity Learning Z Kang, C Peng, Q Cheng Neurocomputing 267, 210-219, 2017 | 109 | 2017 |
| Structured Graph Learning for Scalable Subspace Clustering: From Single-view to Multi-view Z Kang, Z Lin, X Zhu, W Xu IEEE Transactions on Cybernetics 52 (9), 8976 - 8986, 2022 | 89 | 2022 |
| Unified Spectral Clustering with Optimal Graph Z Kang, C Peng, Q Cheng, Z Xu The Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18), 2018 | 83 | 2018 |
| Self-weighted Multiple Kernel Learning for Graph-based Clustering and Semi-supervised Classification Z Kang, X Lu, J Yi, Z Xu The 27th International Joint Conference on Artificial Intelligence (IJCAI-18), 2018 | 81 | 2018 |
| Twin Learning for Similarity and Clustering: A Unified Kernel Approach Z Kang, C Peng, Q Cheng Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17), 2017 | 80 | 2017 |
| Structured Graph Learning for Clustering and Semi-supervised Classification Z Kang, C Peng, Q Cheng, X Liu, X Peng, Z Xu, L Tian Pattern Recognition 110, 107627, 2021 | 72 | 2021 |
| Self-weighted multi-view clustering with soft capped norm S Huang, Z Kang, Z Xu Knowledge-Based Systems 158, 1-8, 2018 | 72 | 2018 |
| Subspace clustering using log-determinant rank approximation C Peng, Z Kang, huiqing li, qiang Cheng ACM KDD 2015, 2015 | 67 | 2015 |
| High-resolution gamma-ray spectroscopy with a microwave-multiplexed transition-edge sensor array O Noroozian, JAB Mates, DA Bennett, JA Brevik, JW Fowler, J Gao, ... Applied Physics Letters 103 (20), 202602, 2013 | 67 | 2013 |
| Pseudo-supervised Deep Subspace Clustering J Lv, Z Kang*, X Lu, Z Xu IEEE Transactions on Image Processing 30, 5252-5263, 2021 | 61 | 2021 |
| Auto-weighted multi-view co-clustering with bipartite graphs S Huang, Z Xu, IW Tsang, Z Kang Information Sciences 512, 18-30, 2020 | 60 | 2020 |
Zenglin XuHarbin Institute of Technology, Shenzhen & Peng Cheng Lab在 hit.edu.cn 的电子邮件经过验证
