Qi Qian

Qi Qian


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


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.

Research Interests

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

Computer Vision: Fine-grained Visual Categorization, Representations 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

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 33th 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 31th 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]


Q. Qian, I. Baytas, R. Jin, A. Jain, S. Zhu. Similarity Learning via Adaptive Regression and Its Application to Image Retrieval. arXiv:1512.01728, 2015.
Q. Qian, R. Jin, L. Zhang and S. Zhu. Towards Making High Dimensional Distance Metric Learning Practical (Code can be found from our CVPR'15 paper). arXiv:1509.04355, 2015.

Professional Services

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

PC Member/Conference Reviewer: ICML18, NeurIPS18, AAAI19, ICLR19, PAKDD19, IJCAI19, ICCV19, NeurIPS19, AAAI20
Last modifed on Jun 7, 2019 by Qi Qian.