Qi Qian's Homepage

Qi Qian

Ph.D.

DAMO Academy, Alibaba Group
Email: qi.qian [at] alibaba-inc [dot] com

Biography

I joined Alibaba in 2015. Before that, I obtained the Ph.D. degree in Computer Science from Department of Computer Science and Engineering, Michigan State University in August 2015, under the supervision of Dr. Rong Jin .

I received my B.Sc. and M.Sc. degrees in Computer Science from Nanjing University in June 2008 and June 2011, respectively. As a master student, I joined the LAMDA group and my supervisor was Dr. Zhi-Hua Zhou.

We are hiring research interns in Hangzhou and Seattle. We look for candidates, who have a strong background on deep learning and can spend more than 3 months with us. If you are interested, please send me your resume via email.

Research Interests

Machine Learning: Distance Metric Learning, Multiple Clustering, Online Learning

Computer Vision: Fine-grained Visual Categorization, Representation Learning, Object Detection

Full Publication List

Google Scholar

Selected Publications

Journal Articles

	J. Hu, Q. Qian, J. Pei, R. Jin and S. Zhu. Finding Multiple Stable Clusterings. Knowledge and Information Systems (KAIS), 2016. DOI:10.1007/s10115-016-0998-9. ["Bests of ICDM 2015"]
	Q. Qian, R. Jin, J. Yi, L. Zhang and S. Zhu. Efficient Distance Metric Learning by Adaptive Sampling and Mini-Batch Stochastic Gradient Descent (SGD). Machine Learning Journal (MLJ), 2015.

Conference Papers

	Z. Liu, Y. Xu, Y. Xu, Q. Qian, H. Li, X. Ji, A. Chan, R. Jin. Improved Fine-Tuning by Better Leveraging Pre-Training Data. In: Proceedings of the 36th Conference on Neural Information Processing Systems (NeurIPS'22), New Orleans, LA, 2022. [Pre-Print PDF] [Code]
	Q. Qian, Y. Xu, J. Hu, H. Li, R. Jin. Unsupervised Visual Representation Learning by Online Constrained K-Means. In: Proceedings of the 35th IEEE Conference on Computer Vision and Pattern Recognition (CVPR'22), New Orleans, LA, 2022. [Pre-Print PDF] [Code]
	Q. Qian, H. Li, J. Hu. Improved Knowledge Distillation via Full Kernel Matrix Transfer. In: Proceedings of the SIAM International Conference on Data Mining (SDM'22), Alexandria, VA, 2022. [Pre-Print PDF] [Code]
	Y. Xu, Q. Qian, J. Hu, H. Li, R. Jin. Weakly Supervised Representation Learning with Coarse Labels. In: Proceedings of the International Conference on Computer Vision (ICCV'21), Virtual, 2021. [Pre-Print PDF] [Code]
	Y. Xu, L. Shang, J. Ye, Q. Qian, Y. Li, B. Sun, H. Li, R. Jin. Dash: Semi-Supervised Learning with Dynamic Thresholding. In: Proceedings of the 38th International Conference on Machine Learning (ICML'21), Virtual, 2021. [Pre-Print PDF] [Code]
	Q. Qian, L. Chen, H. Li, R. Jin. DR Loss: Improving Object Detection by Distributional Ranking. In: Proceedings of the 33rd IEEE Conference on Computer Vision and Pattern Recognition (CVPR'20), Seattle, WA, 2020. [Pre-Print PDF] [Code]
	Q. Qian, J. Hu, H. Li. Hierarchically Robust Representation Learning. In: Proceedings of the 33rd IEEE Conference on Computer Vision and Pattern Recognition (CVPR'20), Seattle, WA, 2020. [Pre-Print PDF] [Concepts in ImageNet]
	Q. Qian, L. Shang, B. Sun, J. Hu, H. Li, R. Jin. SoftTriple Loss: Deep Metric Learning Without Triplet Sampling. In: Proceedings of the International Conference on Computer Vision (ICCV'19), Seoul, Korea, 2019. [PDF] [Code]
	Q. Qian, S. Zhu, J. Tang, R. Jin, B. Sun, H. Li. Robust Optimization over Multiple Domains. In: Proceedings of the 33rd AAAI Conference on Artifical Intelligence (AAAI'19), Honolulu, HI, 2019. [Pre-Print PDF]
	Q. Qian, J. Tang, H. Li, S. Zhu and R. Jin. Large-scale Distance Metric Learning with Uncertainty. In: Proceedings of the 31st IEEE Conference on Computer Vision and Pattern Recognition (CVPR'18), Salt Lake City, UT, 2018. [Spotlight] [PDF]
	G. Liu, Q. Qian, Z. Wang, Q. Zhao, T. Wang, H. Li, J. Xue, S. Zhu, R. Jin and T. Zhao. The Opensesame NIST 2016 Speaker Recognition Evaluation System. In: Proceedings of the INTERSPEECH (INTERSPEECH'17), Stockholm, Sweden, 2017.
	J. Hu, Q. Qian, J. Pei, R. Jin and S. Zhu. Finding Multiple Stable Clusterings. In: Proceedings of the 15th IEEE International Conference on Data Mining (ICDM'15), Atlantic City, NJ, 2015. [Invited to KAIS SI on "Bests of ICDM 2015"]
	Q. Qian, R. Jin, S. Zhu and Y. Lin. Fine-Grained Visual Categorization via Multi-stage Metric Learning. In: Proceedings of the 28th IEEE Conference on Computer Vision and Pattern Recognition (CVPR'15), Boston, MA, 2015. [PDF] [Code]
	Q. Qian, J. Hu, R. Jin, J. Pei and S. Zhu. Distance Metric Learning using Dropout: A Structured Regularization Approach. In: Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'14), New York, NY, 2014. [PDF]
	J. Yi, L. Zhang, R. Jin, Q. Qian and A. K. Jain. Semi-supervised Clustering by Input Pattern Assisted Pairwise Similarity Matrix Completion. In: Proceedings of the 30th International Conference on Machine Learning (ICML'13), Atlanta, GA, 2013. [PDF]

Professional Services

Journal Reviewer: TPAMI, TKDD, TIP, TMM, TBD, EAAI, NEUCOM

Senior PC: IJCAI21

PC Member/Conference Reviewer: CVPR(20, 21, 22), ICCV(19, 21), ECCV(22), ICML(18, 21, 22), NeurIPS(18, 19, 20, 22), ICLR(19, 20), KDD(22), AAAI(19, 20, 21), IJCAI(19, 20, 22)

Last modifed on Feb. 2, 2023 by Qi Qian.