| Structured autoencoders for subspace clustering X Peng, J Feng, S Xiao, WY Yau, JT Zhou, S Yang IEEE Transactions on Image Processing 27 (10), 5076-5086, 2018 | 255 | 2018 |
| Constructing the L2-graph for robust subspace learning and subspace clustering X Peng, Z Yu, Z Yi, H Tang IEEE transactions on cybernetics 47 (4), 1053-1066, 2016 | 219 | 2016 |
| Deep Subspace Clustering with Sparsity Prior. X Peng, S Xiao, J Feng, WY Yau, Z Yi The 25th International Joint Conference on Artificial Intelligence (IJCAI …, 2016 | 210 | 2016 |
| Mobility-aware caching for content-centric wireless networks: Modeling and methodology R Wang, X Peng, J Zhang, KB Letaief IEEE Communications Magazine 54 (8), 77-83, 2016 | 190 | 2016 |
| Denoising MR spectroscopic imaging data with low-rank approximations HM Nguyen, X Peng, MN Do, ZP Liang IEEE Transactions on Biomedical Engineering 60 (1), 78-89, 2012 | 155 | 2012 |
| Scalable sparse subspace clustering X Peng, L Zhang, Z Yi Proceedings of the IEEE conference on computer vision and pattern …, 2013 | 154 | 2013 |
| Connections between nuclear-norm and frobenius-norm-based representations X Peng, C Lu, Z Yi, H Tang IEEE transactions on neural networks and learning systems 29 (1), 218-224, 2016 | 140 | 2016 |
| Anomalynet: An anomaly detection network for video surveillance JT Zhou, J Du, H Zhu, X Peng, Y Liu, RSM Goh IEEE Transactions on Information Forensics and Security 14 (10), 2537-2550, 2019 | 135 | 2019 |
| A unified framework for representation-based subspace clustering of out-of-sample and large-scale data X Peng, H Tang, L Zhang, Z Yi, S Xiao IEEE transactions on neural networks and learning systems 27 (12), 2499-2512, 2015 | 132 | 2015 |
| Quantized densely connected u-nets for efficient landmark localization Z Tang, X Peng, S Geng, L Wu, S Zhang, D Metaxas Proceedings of the European conference on computer vision (ECCV), 339-354, 2018 | 129 | 2018 |
| Learning to learn single domain generalization F Qiao, L Zhao, X Peng Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 126 | 2020 |
| COMIC: Multi-view clustering without parameter selection X Peng, Z Huang, J Lv, H Zhu, JT Zhou International conference on machine learning, 5092-5101, 2019 | 123 | 2019 |
| CR-GAN: learning complete representations for multi-view generation Y Tian, X Peng, L Zhao, S Zhang, DN Metaxas arXiv preprint arXiv:1806.11191, 2018 | 117 | 2018 |
| 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 | 111 | 2020 |
| Robust subspace clustering via thresholding ridge regression X Peng, Z Yi, H Tang Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015 | 108 | 2015 |
| Adaptive dictionary learning in sparse gradient domain for image recovery Q Liu, S Wang, L Ying, X Peng, Y Zhu, D Liang IEEE Transactions on Image Processing 22 (12), 4652-4663, 2013 | 104 | 2013 |
| Learning locality-constrained collaborative representation for robust face recognition X Peng, L Zhang, Z Yi, KK Tan Pattern Recognition 47 (9), 2794-2806, 2014 | 97 | 2014 |
| Deep clustering with sample-assignment invariance prior X Peng, H Zhu, J Feng, C Shen, H Zhang, JT Zhou IEEE transactions on neural networks and learning systems 31 (11), 4857-4868, 2019 | 95 | 2019 |
| Automatic subspace learning via principal coefficients embedding X Peng, J Lu, Z Yi, R Yan IEEE transactions on cybernetics 47 (11), 3583-3596, 2016 | 88 | 2016 |
| Transfer hashing: From shallow to deep JT Zhou, H Zhao, X Peng, M Fang, Z Qin, RSM Goh IEEE transactions on neural networks and learning systems 29 (12), 6191-6201, 2018 | 85 | 2018 |
