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Quanquan Gu

Position: Assistant Professor
Office: Olsson 101F
Phone: 434-243-3428
Fax:
Email: qg5w@virginia.edu
Personal Homepage

Degrees:
Ph.D. Computer Science, University of Illinois at Urbana-Champaign, 2014
M.S. Automation, Tsinghua University, 2010
B.E. Automation, Tsinghua University, 2007

Biography:

Quanquan Gu is an Assistant Professor in the Department of Systems and Information Engineering at the University of Virginia. Prior to joining the University of Virginia, Dr. Gu was a Postdoctoral Research Associate in the Department of Operations Research and Financial Engineering at Princeton University. He received IBM Ph.D. Fellowship in 2013 when he was pursuing his Ph.D. degree in the Department of Computer Science, University of Illinois at Urbana-Champaign. His current research focuses on Machine Learning, High-dimensional Statistical Inference, Data Mining and Optimization.

Research Interests:

  • Machine Learning
  • High-dimensional Statistical Inference
  • Data Mining
  • Optimization

Research Groups:

Research Centers:

Representative Publications:

  1. Zhaoran Wang and Quanquan Gu and Han Liu (2016). On the Statistical Limits of Convex Relaxations: A Case Study. In Proc. of the 33th International Conference on Machine Learning (ICML), New York, USA.
  2. Huan Gui and Jiawei Han and Quanquan Gu (2016). Towards Faster Rates and Oracle Property for Low-Rank Matrix Estimation. In Proc. of the 33th International Conference on Machine Learning (ICML), New York, USA.
  3. Rongda Zhu and Quanquan Gu (2015). Towards a Lower Sample Complexity for Robust One-bit Compressed Sensing. In Proc. of the 32nd International Conference on Machine Learning (ICML'15), Lille, France.
  4. Zhaoran Wang, Quanquan Gu, Yang Ning, and Han Liu (2015). High Dimensional Expectation-Maximization Algorithm: Statistical Optimization and Asymptotic Normality. In Proc. of Advances in Neural Information Processing Systems (NIPS) 28, Montreal, Quebec, Canada, 2015.
  5. Quanquan Gu, Zhaoran Wang, Han Liu (2014). Sparse PCA with Oracle Property. in Proc. of Advances in Neural Information Processing Systems (NIPS’14) 27, Montreal, Quebec, Canada.
  6. Quanquan Gu, Huan Gui, Jiawei Han (2014). Robust Tensor Decomposition with Gross Corruption. in Proc. of Advances in Neural Information Processing Systems (NIPS’14) 27, Montreal, Quebec, Canada.
  7. Quanquan Gu, Charu Aggarwal, Jialu Liu, Jiawei Han (2013). Selective Sampling on Graphs for Classification. in Proc. of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD’13), Chicago, USA, pp.131-139.
  8. Quanquan Gu, Tong Zhang, Chris Ding, Jiawei Han (2012). Selective Labeling via Error Bound Minimization. in Proc. of Advances in Neural Information Processing Systems (NIPS’12) 25, Lake Tahoe, Nevada, United States, pp.332-340.

Other Activities:

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