| Robust PCA via Nonconvex Rank Approximation Z Kang, C Peng, Q Cheng The IEEE International Conference on Data Mining (ICDM 2015), 2015 | 74 | 2015 |
| Kernel-driven Similarity Learning Z Kang, C Peng, Q Cheng Neurocomputing 267, 210-219, 2017 | 68 | 2017 |
| Top-N Recommender System via Matrix Completion Z Kang, C Peng, Q Cheng Thirtieth AAAI Conference on Artificial Intelligence(AAAI-16), 2016 | 68 | 2016 |
| 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 | 54 | 2013 |
| Low-rank Kernel Learning for Graph-based Clustering Z Kang, L Wen, W Chen, Z Xu Knowledge-Based Systems 163, 510-517, 2019 | 53 | 2019 |
| Robust Graph Learning from Noisy Data Z Kang, H Pan, SCH Hoi, Z Xu IEEE Transactions on Cybernetics 50 (5), 1833-1843, 2020 | 48 | 2020 |
| Subspace clustering using log-determinant rank approximation C Peng, Z Kang, huiqing li, qiang Cheng ACM KDD 2015, 2015 | 41 | 2015 |
| Self-weighted multi-view clustering with soft capped norm S Huang, Z Kang, Z Xu Knowledge-Based Systems 158, 1-8, 2018 | 36 | 2018 |
| Robust Subspace Clustering via Smoothed Rank Approximation Z Kang, P Chong, C Qiang IEEE Signal Processing Letters 22 (11), 2088-2092, 2015 | 36 | 2015 |
| 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 | 35 | 2018 |
| Subspace Clustering via Variance Regularized Ridge Regression C Peng, Z Kang, Q Cheng Conference on Computer Vision and Pattern Recognition (CVPR 2017), 2017 | 34 | 2017 |
| 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 | 34 | 2017 |
| Auto-weighted multi-view clustering via kernelized graph learning S Huang, Z Kang, IW Tsang, Z Xu Pattern Recognition 88, 174-184, 2019 | 33 | 2019 |
| Feature Selection Embedded Subspace Clustering C Peng, Z Kang, M Yang, Q Cheng IEEE Signal Processing Letters, 2016 | 31 | 2016 |
| 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 | 23 | 2018 |
| LogDet Rank Minimization with Application to Subspace Clustering kang zhao, P Chong, C Jie, C Qiang Computational Intelligence and Neuroscience 2015, 2015 | 23 | 2015 |
| Clustering with Similarity Preserving Z Kang, H Xu, B Wang, H Zhu, Z Xu Neurocomputing, 2019 | 21 | 2019 |
| Robust subspace clustering via tighter rank approximation zhao kang, P Chong, C Qiang ACM CIKM'15, 2015 | 20 | 2015 |
| Nonnegative Matrix Factorization with Integrated Graph and Feature Learning C Peng, Z Kang, Y Hu, Q Cheng ACM Transactions on Intelligent Systems and Technology 8 (3), 2017 | 18 | 2017 |
| Integrate and Conquer: Double-Sided Two-Dimensional k-Means Via Integrating of Projection and Manifold Construction C Peng, Z Kang, S Cai, Q Cheng ACM Transactions on Intelligent Systems and Technology (TIST) 9 (5), 1-25, 2018 | 17 | 2018 |
Qiang ChengU Kentucky, U Illinois-Urbana Champaign, WayneState, Siemens Med/Corp Research, SIUCVerified email at uky.edu
