Xingguo Li — Home

I am a Quantitative Researcher at Radix. Prior to Radix, I was a Postdoctoral Research Associate in the Computer Science Department at Princeton University, working with Prof. Sanjeev Arora. Before that, I received my Ph.D. in the Department of Electrical and Computer Engineering, University of Minnesota, under the supervision of Prof. Jarvis Haupt.

Here is my CV and Google Scholar profile.

Research Interest

My research interests generally include machine learning, deep learning, and optimization, with application in quantitative trading, data science, and applications.

Selected Publications

• “Symmetry, Saddle Points, and Global Geometry of Nonconvex Matrix Factorization” [slide]
  Xingguo Li, Zhaoran Wang, Junwei Lu, Raman Arora, Jarvis Haupt, Han Liu, and Tuo Zhao
  IEEE Transactions on Information Theory (TIT), vol. 65, no. 6, pp. 3489 - 3514, 2019
  

• “Picasso: A Sparse Learning Library for High Dimensional Data Analysis in R and Python” [github]
  Xingguo Li*, Jian Ge*, Haoming Jiang, Han Liu, Tong Zhang, Mengdi Wang, and Tuo Zhao
  Journal of Machine Learning Research (JLMR), vol. 20, pp. 1 - 5, 2019
  (*Best Student Paper Award *)
  

• “ZO-AdaMM: Zeroth-Order Adaptive Momentum Method for Black-Box Optimization”
  Xiangyi Chen, Sijia Liu, Kaidi Xu, Xingguo Li, Due Lin, Mingyi Hong, and David Cox
  Neural Information Processing Systems (NeurIPS), 2019
  

• “NOODL: Provable Online Dictionary Learning and Sparse Coding”
  Sirisha Rambhatla, Xingguo Li, and Jarvis Haupt
  International Conference on Learning Representations (ICLR), 2019
  

• “Towards Black-box Iterative Machine Teaching”
  Weiyang Liu, Bo Dai, Xingguo Li, Zhen Liu, James Rehg, Le Song
  International Conference on Machine Learning (ICML), 2018
  

• “On Faster Convergence of Cyclic Block Coordinate Descent-type Methods for Strongly Convex Minimization”
  Xingguo Li, Tuo Zhao, Raman Arora, Han Liu, and Mingyi Hong
  Journal of Machine Learning Research (JLMR), vol. 18, no. 184, pp. 1 - 24, 2018
  

• “On Quadratic Convergence of DC Proximal Newton Algorithm in Nonconvex Sparse Learning”
  Xingguo Li, Lin Yang, Jian Ge, Jarvis Haupt, Tong Zhang, and Tuo Zhao
  Neural Information Processing Systems (NIPS), 2017 (short version)
  

• “Near Optimal Sketching of Low-Rank Tensor Regression”
  Jarvis Haupt, Xingguo Li, and David Woodruff  (α - β order)
  Neural Information Processing Systems (NIPS), 2017
  

• “Deep Hyperspherical Learning”
  Weiyang Liu, Yan-Ming Zhang, Xingguo Li, Zhiding Yu, Bo Dai, Tuo Zhao, and Le Song
  Neural Information Processing Systems (NIPS), 2017  (*Spotlight*)
  

• “Stochastic Variance Reduced Optimization for Nonconvex Sparse Learning” [slide]
  Xingguo Li, Tuo Zhao, Raman Arora, Han Liu, and Jarvis Haupt
  International Conference on Machine Learning (ICML), 2016
  

• “Identifying Outliers in Large Matrices via Randomized Adaptive Compressive Sampling” [slide]
  Xingguo Li and Jarvis Haupt
  IEEE Transactions on Signal Processing (TSP), vol. 63, no. 7, pp. 1792 - 1807, 2015
  

• “The flare Package for High Dimensional Linear Regression and Precision Matrix Estimation in R”
  Xingguo Li*, Tuo Zhao*, Lie Wang, Xiaoming Yuan, and Han Liu
  Journal of Machine Learning Research (JLMR), vol. 16, pp. 553 - 557, 2015
  

• “Locating Salient Group-Structured Image Features via Adaptive Compressive Sensing” [slide]
  Xingguo Li and Jarvis Haupt
  IEEE Global Conference on Signal and Information Processing (GlobalSIP), 2015
  (*Best Student Paper Award*)
  

Experience

• Postdoctoral Research Associate, September 2018 — Present
  Department of Computer Science, Princeton University
  Supervisor: Prof. Sanjeev Arora
  

• Visiting Graduate Scholar, March 2017 — April 2018
  School of Industrial & Systems Engineering, Georgia Institute of Technology
  Host: Prof. Tuo Zhao
  

• Visiting Researcher, August 2016 — September 2016
  IBM Research Almaden
  Host: Prof. David P. Woodruff
  

• Visiting Graduate Scholar, May 2016 — August 2016
  Department of Computer Science, Johns Hopkins University
  Host: Prof. Raman Arora
  

• Graduate Research Assistant, September 2013 — July 2018
  Department of Electrical and Computer Engineering, University of Minnesota
  Supervisor: Prof. Jarvis Haupt
  

• Research Associate, August 2010 — June 2011
  School of Computer Science, Carnegie Mellon University
  Supervisor: Prof. Fernando De la Torre and Prof. Alexander G. Hauptmann

Selected Awards

• (March 2018) I was awarded IBM Herman Goldstine Memorial Postdoctoral Fellowship. (Declined and joined the Princeton University)

• (August 2017) I was awarded 2017-18 Doctoral Dissertation Fellowship by University of Minnesota Twin Cities.
  

• (July 2017) Out paper “Target Based Hyperspectral Demixing via Generalized Robust PCA” was in the Best Student Paper Award Finalist at the 2017 Asilomar Conference on Signals, Systems, and Computers (Asilomar).

• (January 2016) Our paper “The picasso Package for Nonconvex Regularized M-estimation in High Dimensions in R” received the Best Student Paper Award from the American Statistical Association Statistical Computing Section.
  

• (November 2015) Our paper “Locating Salient Group-Structured Image Features via Adaptive Compressive Sensing” received the Best Student Paper Award at the 2015 Global Conference on Signal and Information Processing (GlobalSIP).
  

• (Summer of 2014 — 2016) I was awarded Google Summer of Code.
  

• (May 2013) I received the Outstanding Graduate Award of Class 2013 form the Department of of Mathematics and Statistics, University of Minnesota Duluth.
  

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