Xingguo Li

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Tuo ZhaoAssociate Professor, Georgia TechVerified email at gatech.edu
Jarvis HauptAssociate Professor of Electrical and Computer Engineering, University of MinnesotaVerified email at umn.edu
Han LiuOrrington Lunt Professor of Computer Science, Statistics and Data Science, Northwestern UniversityVerified email at northwestern.edu
Raman AroraDepartment of Computer Science, Johns Hopkins UniversityVerified email at cs.jhu.edu
Mingyi HongAssociate Professor, University of Minnesota; Amazon ScholarVerified email at umn.edu
Zhaoran WangAssociate Professor at Northwestern UniversityVerified email at northwestern.edu
Junwei LuAssistant Professor of Biostatistics, Harvard T.H. Chan School of Public HealthVerified email at hsph.harvard.edu
Sirisha RambhatlaAssistant Professor at the University of WaterlooVerified email at umn.edu
Tong ZhangUIUCVerified email at tongzhang-ml.org
Le SongBiomap, Mohamed bin Zayed University of Artificial IntelligenceVerified email at biomap.com
Bo DaiGoogle Brain & Georgia TechVerified email at google.com
Weiyang LiuUniversity of Cambridge & Max Planck Institute for Intelligent SystemsVerified email at cam.ac.uk
Kathryn RoederProfessor of Statistics, Carnegie Mellon UniversityVerified email at andrew.cmu.edu
Sijia LiuMichigan State University & MIT-IBM Watson AI LabVerified email at msu.edu
Larry WassermanProfessor, Department of Statistics and Machine Learning Department, Carnegie Mellon UniversityVerified email at stat.cmu.edu
Mengdi WangCenter for Statistics & Machine Learning, ECE, Princeton UniversityVerified email at princeton.edu
Lin F. Yang (杨林)Assistant Professor, Department of Electrical and Computer Engineering @ UCLAVerified email at ee.ucla.edu
James M. RehgFounder Professor of Computer Science, University of Illinois at Urbana-ChampaignVerified email at illinois.edu
Sanjeev AroraProfessor of Computer Science, Princeton UniversityVerified email at cs.princeton.edu
Simon Shaolei DuAssistant Professor, School of Computer Science and Engineering, University of WashingtonVerified email at cs.washington.edu

Xingguo Li

Radix Trading

Verified email at radix-trading.com - Homepage

machine learning optimization signal processing


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Deep hyperspherical learning W Liu, YM Zhang, X Li, Z Yu, B Dai, T Zhao, L Song Advances in neural information processing systems 30, 2017	152	2017
The flare package for high dimensional linear regression and precision matrix estimation in R X Li, T Zhao, X Yuan, H Liu Journal of Machine Learning Research, 553-557, 2015	132*	2015
Symmetry, Saddle Points, and Global Optimization Landscape of Nonconvex Matrix Factorization X Li, J Lu, R Arora, J Haupt, H Liu, Z Wang, T Zhao IEEE Transactions on Information Theory 65 (6), 3489 - 3514, 2019	114*	2019
Stochastic variance reduced optimization for nonconvex sparse learning X Li, T Zhao, R Arora, H Liu, J Haupt Proceedings of the 33rd International Conference on Machine Learning, 917-925, 2016	111*	2016
Zo-adamm: Zeroth-order adaptive momentum method for black-box optimization X Chen, S Liu, K Xu, X Li, X Lin, M Hong, D Cox Advances in neural information processing systems 32, 2019	110	2019
huge: High-dimensional undirected graph estimation T Zhao, X Li, H Liu, K Roeder, J Lafferty, L Wasserman URL http://CRAN. R-project. org/package= huge. R package version 1 (7), 2015	81*	2015
On tighter generalization bound for deep neural networks: Cnns, resnets, and beyond X Li, J Lu, Z Wang, J Haupt, T Zhao arXiv preprint arXiv:1806.05159, 2018	72	2018
On Generalization Bounds of a Family of Recurrent Neural Networks M Chen, X Li, T Zhao International Conference on Artificial Intelligence and Statistics (arXiv …, 2020	67	2020
Towards black-box iterative machine teaching W Liu, B Dai, X Li, Z Liu, J Rehg, L Song International Conference on Machine Learning, 3141-3149, 2018	67	2018
Identifying Outliers in Large Matrices via Randomized Adaptive Compressive Sampling X Li, J Haupt IEEE Trans. Signal Processing, 1792-1807, 2015	61	2015
An Improved Convergence Analysis of Cyclic Block Coordinate Descent-type Methods for Strongly Convex Minimization X Li, T Zhao, R Arora, H Liu, M Hong Proceedings of the 19th International Conference on Artificial Intelligence …, 2016	53*	2016
Over-parameterized adversarial training: An analysis overcoming the curse of dimensionality Y Zhang, O Plevrakis, SS Du, X Li, Z Song, S Arora Advances in Neural Information Processing Systems 33, 679-688, 2020	52	2020
On computation and generalization of generative adversarial imitation learning M Chen, Y Wang, T Liu, Z Yang, X Li, Z Wang, T Zhao arXiv preprint arXiv:2001.02792, 2020	48	2020
Near optimal sketching of low-rank tensor regression X Li, J Haupt, D Woodruff Advances in Neural Information Processing Systems 30, 2017	39	2017
Picasso: A Sparse Learning Library for High Dimensional Data Analysis in R and Python J Ge, X Li, H Jiang, H Liu, T Zhang, M Wang, T Zhao Journal of Machine Learning Research, 2019	33*	2019
Zeroth-order stochastic projected gradient descent for nonconvex optimization S Liu, X Li, PY Chen, J Haupt, L Amini 2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP …, 2018	28	2018
A First Order Free Lunch for SQRT-Lasso X Li, J Haupt, R Arora, H Liu, M Hong, T Zhao arXiv preprint arXiv:1605.07950, 2016	23*	2016
Noodl: Provable online dictionary learning and sparse coding S Rambhatla, X Li, J Haupt arXiv preprint arXiv:1902.11261, 2019	21	2019
On constrained nonconvex stochastic optimization: A case study for generalized eigenvalue decomposition Z Chen, X Li, L Yang, J Haupt, T Zhao The 22nd International Conference on Artificial Intelligence and Statistics …, 2019	20*	2019
On quadratic convergence of DC proximal Newton algorithm in nonconvex sparse learning X Li, L Yang, J Ge, J Haupt, T Zhang, T Zhao Advances in neural information processing systems 30, 2017	16	2017

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