| 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 | 246 | 2020 |
| Denoising of hyperspectral images using nonconvex low rank matrix approximation Y Chen, Y Guo, Y Wang, D Wang, C Peng, G He IEEE Transactions on Geoscience and Remote Sensing 55 (9), 5366-5380, 2017 | 213 | 2017 |
| Robust PCA via nonconvex rank approximation Z Kang, C Peng, Q Cheng 2015 IEEE International Conference on Data Mining, 211-220, 2015 | 200 | 2015 |
| Low-rank tensor graph learning for multi-view subspace clustering Y Chen, X Xiao, C Peng, G Lu, Y Zhou IEEE Transactions on Circuits and Systems for Video Technology 32 (1), 92-104, 2021 | 155 | 2021 |
| Generalized nonconvex low-rank tensor approximation for multi-view subspace clustering Y Chen, S Wang, C Peng, Z Hua, Y Zhou IEEE Transactions on Image Processing 30, 4022-4035, 2021 | 136 | 2021 |
| 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 | 136 | 2021 |
| Top-n recommender system via matrix completion Z Kang, C Peng, Q Cheng Proceedings of the AAAI conference on artificial intelligence 30 (1), 2016 | 132 | 2016 |
| Kernel-driven similarity learning Z Kang, C Peng, Q Cheng Neurocomputing 267, 210-219, 2017 | 131 | 2017 |
| Exploring rich and efficient spatial temporal interactions for real-time video salient object detection C Chen, G Wang, C Peng, Y Fang, D Zhang, H Qin IEEE Transactions on Image Processing 30, 3995-4007, 2021 | 108 | 2021 |
| Improved robust video saliency detection based on long-term spatial-temporal information C Chen, G Wang, C Peng, X Zhang, H Qin IEEE transactions on image processing 29, 1090-1100, 2019 | 108 | 2019 |
| Unified spectral clustering with optimal graph Z Kang, C Peng, Q Cheng, Z Xu Proceedings of the AAAI conference on artificial intelligence 32 (1), 2018 | 108 | 2018 |
| Twin learning for similarity and clustering: A unified kernel approach Z Kang, C Peng, Q Cheng Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017 | 102 | 2017 |
| Improved saliency detection in RGB-D images using two-phase depth estimation and selective deep fusion C Chen, J Wei, C Peng, W Zhang, H Qin IEEE Transactions on Image Processing 29, 4296-4307, 2020 | 99 | 2020 |
| Depth-quality-aware salient object detection C Chen, J Wei, C Peng, H Qin IEEE Transactions on Image Processing 30, 2350-2363, 2021 | 96 | 2021 |
| Subspace clustering using log-determinant rank approximation C Peng, Z Kang, H Li, Q Cheng Proceedings of the 21th ACM SIGKDD international conference on Knowledge …, 2015 | 85 | 2015 |
| Discriminative ridge machine: A classifier for high-dimensional data or imbalanced data C Peng, Q Cheng IEEE transactions on neural networks and learning systems 32 (6), 2595-2609, 2020 | 69 | 2020 |
| Robust principal component analysis: A factorization-based approach with linear complexity C Peng, Y Chen, Z Kang, C Chen, Q Cheng Information Sciences 513, 581-599, 2020 | 67 | 2020 |
| Subspace clustering via variance regularized ridge regression C Peng, Z Kang, Q Cheng Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 66 | 2017 |
| Logdet rank minimization with application to subspace clustering Z Kang, C Peng, J Cheng, Q Cheng Computational intelligence and neuroscience 2015 (1), 824289, 2015 | 66 | 2015 |
| Feature selection embedded subspace clustering C Peng, Z Kang, M Yang, Q Cheng IEEE Signal Processing Letters 23 (7), 1018-1022, 2016 | 56 | 2016 |