| Softtriple loss: Deep metric learning without triplet sampling Q Qian, L Shang, B Sun, J Hu, H Li, R Jin Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 528 | 2019 |
| Exact and consistent interpretation for piecewise linear neural networks: A closed form solution L Chu, X Hu, J Hu, L Wang, J Pei Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 2018 | 139 | 2018 |
| Towards discovering what patterns trigger what labels YF Li, JH Hu, Y Jiang, ZH Zhou Proceedings of the AAAI conference on artificial intelligence 26 (1), 1012-1018, 2012 | 72 | 2012 |
| Subspace multi-clustering: a review J Hu, J Pei Knowledge and information systems 56 (2), 257-284, 2018 | 58 | 2018 |
| Finding multiple stable clusterings J Hu, Q Qian, J Pei, R Jin, S Zhu Knowledge and Information Systems 51 (3), 991-1021, 2017 | 48 | 2017 |
| Unsupervised visual representation learning by online constrained k-means Q Qian, Y Xu, J Hu, H Li, R Jin Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 47 | 2022 |
| Distance metric learning using dropout: a structured regularization approach Q Qian, J Hu, R Jin, J Pei, S Zhu Proceedings of the 20th ACM SIGKDD international conference on Knowledge …, 2014 | 38 | 2014 |
| Intra-modal proxy learning for zero-shot visual categorization with clip Q Qian, Y Xu, J Hu Advances in Neural Information Processing Systems 36, 25461-25474, 2023 | 36 | 2023 |
| Multi-modal proxy learning towards personalized visual multiple clustering J Yao, Q Qian, J Hu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 31 | 2024 |
| Online zero-shot classification with clip Q Qian, J Hu European Conference on Computer Vision, 462-477, 2024 | 26 | 2024 |
| Weakly supervised representation learning with coarse labels Y Xu, Q Qian, H Li, R Jin, J Hu Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 17 | 2021 |
| Augdmc: Data augmentation guided deep multiple clustering J Yao, E Liu, M Rashid, J Hu Procedia Computer Science 222, 571-580, 2023 | 16 | 2023 |
| Pairwised specific distance learning from physical linkages J Hu, DC Zhan, X Wu, Y Jiang, ZH Zhou ACM Transactions on Knowledge Discovery from Data (TKDD) 9 (3), 1-27, 2015 | 12 | 2015 |
| Improved visual fine-tuning with natural language supervision J Wang, Y Xu, J Hu, M Yan, J Sang, Q Qian Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 11 | 2023 |
| Improved knowledge distillation via full kernel matrix transfer Q Qian, H Li, J Hu Proceedings of the 2022 SIAM International Conference on Data Mining (SDM …, 2022 | 10* | 2022 |
| Fairness in healthcare AI MA Ahmad, C Eckert, C Allen, V Kumar, J Hu, A Teredesai 2021 IEEE 9th International Conference on Healthcare Informatics (ICHI), 554-555, 2021 | 10 | 2021 |
| Hierarchically robust representation learning Q Qian, J Hu, H Li Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 9 | 2020 |
| Dual-disentangled deep multiple clustering J Yao, J Hu Proceedings of the 2024 SIAM International Conference on Data Mining (SDM …, 2024 | 8 | 2024 |
| Customized multiple clustering via multi-modal subspace proxy learning J Yao, Q Qian, J Hu Advances in Neural Information Processing Systems 37, 82705-82725, 2024 | 7 | 2024 |
| Interpretable phenotyping for electronic health records C Allen, J Hu, V Kumar, MA Ahmad, A Teredesai 2021 IEEE 9th International Conference on Healthcare Informatics (ICHI), 161-170, 2021 | 6 | 2021 |
Qi QianMeta Reality LabsVerified email at meta.com
