| Multi-view clustering via deep matrix factorization H Zhao, Z Ding, Y Fu Proceedings of the AAAI conference on artificial intelligence 31 (1), 2017 | 433 | 2017 |
| Leveraging the invariant side of generative zero-shot learning J Li, M Jing, K Lu, Z Ding, L Zhu, Z Huang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 318 | 2019 |
| 3d human pose estimation with spatial and temporal transformers C Zheng, S Zhu, M Mendieta, T Yang, C Chen, Z Ding Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 313 | 2021 |
| Maximum density divergence for domain adaptation J Li, E Chen, Z Ding, L Zhu, K Lu, HT Shen IEEE transactions on pattern analysis and machine intelligence 43 (11), 3918 …, 2020 | 234 | 2020 |
| Domain invariant and class discriminative feature learning for visual domain adaptation S Li, S Song, G Huang, Z Ding, C Wu IEEE transactions on image processing 27 (9), 4260-4273, 2018 | 216 | 2018 |
| MOGONET integrates multi-omics data using graph convolutional networks allowing patient classification and biomarker identification T Wang, W Shao, Z Huang, H Tang, J Zhang, Z Ding, K Huang Nature Communications 12 (3445), 2021 | 180* | 2021 |
| Robust transfer metric learning for image classification Z Ding, Y Fu IEEE Transactions on Image Processing 26 (2), 660-670, 2016 | 164 | 2016 |
| Low-rank common subspace for multi-view learning Z Ding, Y Fu 2014 IEEE international conference on Data Mining, 110-119, 2014 | 152 | 2014 |
| Adaptive adversarial network for source-free domain adaptation H Xia, H Zhao, Z Ding Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 151 | 2021 |
| From ensemble clustering to multi-view clustering Z Tao, H Liu, S Li, Z Ding, Y Fu IJCAI, 2017 | 149 | 2017 |
| Deep residual correction network for partial domain adaptation S Li, CH Liu, Q Lin, Q Wen, L Su, G Huang, Z Ding IEEE transactions on pattern analysis and machine intelligence 43 (7), 2329-2344, 2020 | 135 | 2020 |
| Deep domain generalization with structured low-rank constraint Z Ding, Y Fu IEEE Transactions on Image Processing 27 (1), 304-313, 2017 | 130 | 2017 |
| Low-rank embedded ensemble semantic dictionary for zero-shot learning Z Ding, M Shao, Y Fu Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 128 | 2017 |
| Graph adaptive knowledge transfer for unsupervised domain adaptation Z Ding, S Li, M Shao, Y Fu Proceedings of the European Conference on Computer Vision (ECCV), 37-52, 2018 | 127 | 2018 |
| Partial multi-view clustering via consistent GAN Q Wang, Z Ding, Z Tao, Q Gao, Y Fu 2018 IEEE International Conference on Data Mining (ICDM), 1290-1295, 2018 | 121 | 2018 |
| Latent low-rank transfer subspace learning for missing modality recognition Z Ding, S Ming, Y Fu Proceedings of the AAAI conference on artificial intelligence 28 (1), 2014 | 117 | 2014 |
| Where and how to transfer: knowledge aggregation-induced transferability perception for unsupervised domain adaptation J Dong, Y Cong, G Sun, Z Fang, Z Ding IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021 | 115 | 2021 |
| Joint adversarial domain adaptation S Li, CH Liu, B Xie, L Su, Z Ding, G Huang Proceedings of the 27th ACM International Conference on Multimedia, 729-737, 2019 | 113 | 2019 |
| Consensus regularized multi-view outlier detection H Zhao, H Liu, Z Ding, Y Fu IEEE Transactions on Image Processing 27 (1), 236-248, 2017 | 112 | 2017 |
| Generative multi-view human action recognition L Wang, Z Ding, Z Tao, Y Liu, Y Fu Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 103 | 2019 |
Yun Raymond FuNEU, COE Distinguished Professor; MAE, FAAAS, FIEEE, FSPIE, FOSA, FIAPRVerified email at neu.edu
