| 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 | 285 | 2019 |
| Fine-grained visual categorization via multi-stage metric learning Q Qian, R Jin, S Zhu, Y Lin Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2015 | 173 | 2015 |
| Efficient distance metric learning by adaptive sampling and mini-batch stochastic gradient descent (SGD) Q Qian, R Jin, J Yi, L Zhang, S Zhu Machine Learning 99, 353-372, 2015 | 96 | 2015 |
| Instant-teaching: An end-to-end semi-supervised object detection framework Q Zhou, C Yu, Z Wang, Q Qian, H Li Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 87 | 2021 |
| Building decision trees for the multi-class imbalance problem TR Hoens, Q Qian, NV Chawla, ZH Zhou Advances in Knowledge Discovery and Data Mining: 16th Pacific-Asia …, 2012 | 87 | 2012 |
| Dash: Semi-supervised learning with dynamic thresholding Y Xu, L Shang, J Ye, Q Qian, YF Li, B Sun, H Li, R Jin International Conference on Machine Learning, 11525-11536, 2021 | 70 | 2021 |
| Dr loss: Improving object detection by distributional ranking Q Qian, L Chen, H Li, R Jin Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 68 | 2020 |
| Robust optimization over multiple domains Q Qian, S Zhu, J Tang, R Jin, B Sun, H Li Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 4739-4746, 2019 | 60 | 2019 |
| Semi-supervised clustering by input pattern assisted pairwise similarity matrix completion J Yi, L Zhang, R Jin, Q Qian, A Jain International conference on machine learning, 1400-1408, 2013 | 55 | 2013 |
| Learning to rank proposals for object detection Z Tan, X Nie, Q Qian, N Li, H Li Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 43 | 2019 |
| Zen-nas: A zero-shot nas for high-performance image recognition M Lin, P Wang, Z Sun, H Chen, X Sun, Q Qian, H Li, R Jin Proceedings of the IEEE/CVF International Conference on Computer Vision, 347-356, 2021 | 37 | 2021 |
| 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 |
| Finding multiple stable clusterings J Hu, Q Qian, J Pei, R Jin, S Zhu Knowledge and Information Systems 51, 991-1021, 2017 | 32 | 2017 |
| Large-scale distance metric learning with uncertainty Q Qian, J Tang, H Li, S Zhu, R Jin Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 25 | 2018 |
| Towards understanding label smoothing Y Xu, Y Xu, Q Qian, H Li, R Jin arXiv preprint arXiv:2006.11653, 2020 | 23 | 2020 |
| Robust gaussian process regression for real-time high precision GPS signal enhancement M Lin, X Song, Q Qian, H Li, L Sun, S Zhu, R Jin Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019 | 17 | 2019 |
| Rbgnet: Ray-based grouping for 3d object detection H Wang, S Shi, Z Yang, R Fang, Q Qian, H Li, B Schiele, L Wang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 15 | 2022 |
| Wemix: How to better utilize data augmentation Y Xu, A Noy, M Lin, Q Qian, H Li, R Jin arXiv preprint arXiv:2010.01267, 2020 | 13 | 2020 |
| Neural architecture design for GPU-efficient networks M Lin, H Chen, X Sun, Q Qian, H Li, R Jin arXiv preprint arXiv:2006.14090, 2020 | 11 | 2020 |
| Error Correction in GPS Signal M Lin, S Xiaomin, Q Qian, L Sun, S Zhu, R Jin US Patent App. 16/235,487, 2020 | 10 | 2020 |
Rong JinAlibaba GroupVerified email at cse.msu.edu
