| 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 | 306 | 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 | 99 | 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 | 58 | 2012 |
| Finding multiple stable clusterings J Hu, Q Qian, J Pei, R Jin, S Zhu Knowledge and Information Systems 51, 991-1021, 2017 | 33 | 2017 |
| 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 | 33 | 2014 |
| Subspace multi-clustering: a review J Hu, J Pei Knowledge and information systems 56, 257-284, 2018 | 31 | 2018 |
| 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 | 13 | 2015 |
| 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 | 9 | 2022 |
| 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 | 5* | 2022 |
| 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 | 4* | 2021 |
| How can I index my thousands of photos effectively and automatically? An unsupervised feature selection approach J Hu, J Pei, J Tang Proceedings of the 2014 SIAM International Conference on Data Mining, 136-144, 2014 | 4 | 2014 |
| Hierarchically robust representation learning Q Qian, J Hu, H Li Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 3 | 2020 |
| Cost-adaptive Neural Networks for Peak Volume Prediction with EMM Filtering B Yu, G Graciani, A Nascimento, J Hu 2019 IEEE International Conference on Big Data (Big Data), 4208-4213, 2019 | 2 | 2019 |
| 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 | 1 | 2021 |
| 一种基于教学模型的协同训练方法 胡菊花， 姜远， 周志华 计算机研究与发展 50 (11), 2262-2268, 2013 | 1 | 2013 |
| NPRL: Nightly Profile Representation Learning for Early Sepsis Onset Prediction in ICU Trauma Patients T Stewart, K Stern, G O'Keefe, A Teredesai, J Hu arXiv preprint arXiv:2304.12737, 2023 | | 2023 |
| Multi-Subset Approach to Early Sepsis Prediction K Ewig, X Lin, T Stewart, K Stern, G O'Keefe, A Teredesai, J Hu arXiv preprint arXiv:2304.06384, 2023 | | 2023 |
| Improved Visual Fine-tuning with Natural Language Supervision J Wang, Y Xu, J Hu, M Yan, J Sang, Q Qian arXiv preprint arXiv:2304.01489, 2023 | | 2023 |
| Enhancing Peak Network Traffic Prediction via Time-Series Decomposition T Stewart, B Yu, A Nascimento, J Hu arXiv preprint arXiv:2303.13529, 2023 | | 2023 |
| Sub-Sequence Graph Representation Learning on High Variability Data for Dynamic Risk Prediction in Critical Care A Teredesai, S Huang, T Stewart, J Hu, A Thakker, K Stern, GE O’Keefe 2022 IEEE International Conference on Big Data (Big Data), 2082-2092, 2022 | | 2022 |
Qi QianAlibaba GroupПотвърден имейл адрес: alibaba-inc.com
