Qing Qu

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John WrightElectrical Engineering, Columbia UniversityVerified email at columbia.edu
Zhihui ZhuAssistant Professor, Ohio State UniversityVerified email at osu.edu
Ju SunAssistant Professor, Computer Science & Engineering, University of Minnesota at Twin CitiesVerified email at umn.edu
Trac D. TranProsessor of Electrical and Computer Engineering, Johns Hopkins UniversityVerified email at jhu.edu
Nasser M NasrabadiProfessor, CSEE, West Virginia UniversityVerified email at mail.wvu.edu
Chong YouGoogleVerified email at google.com
Xiao LiThe Chinese University of Hong Kong, ShenzhenVerified email at cuhk.edu.cn
Yuqian ZhangAssistant Professor, Rutgers UniversityVerified email at rutgers.edu
Xiao Li (李虓)Ph.D. candidate at University of MichiganVerified email at umich.edu
Jinxin ZhouOhio State UniversityVerified email at osu.edu
Sheng LiuStanford UniversityVerified email at stanford.edu
Xiaoxia Sun (孙骁遐)RobloxVerified email at roblox.com
Tianyu Ding, Ph.D.Senior Researcher, Microsoft, Johns Hopkins UniversityVerified email at microsoft.com
Yuexiang ZhaiUC BerkeleyVerified email at berkeley.edu
Can YarasPhD Student, University of MichiganVerified email at umich.edu
Anthony Man-Cho SoDepartment of Systems Engineering and Engineering Management, The Chinese University of Hong KongVerified email at se.cuhk.edu.hk
Shixiang ChenUniversity of Science and Technology of ChinaVerified email at ustc.edu.cn
Zengde DengCainiao AI, Alibaba GroupVerified email at se.cuhk.edu.hk
Yonina EldarMath and Computer Science, WeizmannVerified email at weizmann.ac.il
Carlos Fernandez-GrandaAssociate Professor, Courant Institute and Center for Data Science, New York UniversityVerified email at cims.nyu.edu

Qing Qu

Assistant Professor, Dept. of EECS, University of Michigan

Verified email at umich.edu - Homepage

Machine Learning Nonconvex Optimization High Dimensional Data Analysis Deep Learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
A geometric analysis of phase retrieval J Sun, Q Qu, J Wright Foundations of Computational Mathematics 18, 1131-1198, 2018	562	2018
Complete dictionary recovery over the sphere I: Overview and the geometric picture J Sun, Q Qu, J Wright IEEE Transactions on Information Theory 63 (2), 853-884, 2016	291	2016
When are nonconvex problems not scary? J Sun, Q Qu, J Wright arXiv preprint arXiv:1510.06096, 2015	174	2015
Complete dictionary recovery using nonconvex optimization J Sun, Q Qu, J Wright International Conference on Machine Learning, 2351-2360, 2015	138*	2015
Complete dictionary recovery over the sphere ii: Recovery by riemannian trust-region method J Sun, Q Qu, J Wright IEEE Transactions on Information Theory 63 (2), 885-914, 2016	136	2016
Structured priors for sparse-representation-based hyperspectral image classification X Sun, Q Qu, NM Nasrabadi, TD Tran IEEE geoscience and remote sensing letters 11 (7), 1235-1239, 2013	129	2013
Finding a sparse vector in a subspace: Linear sparsity using alternating directions Q Qu, J Sun, J Wright Advances in Neural Information Processing Systems 27, 2014	118	2014
Abundance estimation for bilinear mixture models via joint sparse and low-rank representation Q Qu, NM Nasrabadi, TD Tran IEEE Transactions on Geoscience and Remote Sensing 52 (7), 4404-4423, 2013	116	2013
A geometric analysis of neural collapse with unconstrained features Z Zhu, T Ding, J Zhou, X Li, C You, J Sulam, Q Qu Advances in Neural Information Processing Systems 34, 29820-29834, 2021	79	2021
Weakly convex optimization over Stiefel manifold using Riemannian subgradient-type methods X Li, S Chen, Z Deng, Q Qu, Z Zhu, AMC So SIAM Journal on Optimization 31 (3), 1605–1634, 2021	57*	2021
Convolutional phase retrieval via gradient descent Q Qu, Y Zhang, YC Eldar, J Wright IEEE Transactions on Information Theory 66 (3), 1785-1821, 2019	51*	2019
From symmetry to geometry: Tractable nonconvex problems Y Zhang, Q Qu, J Wright arXiv preprint arXiv:2007.06753, 2020	44	2020
Robust training under label noise by over-parameterization S Liu, Z Zhu, Q Qu, C You International Conference on Machine Learning, 14153-14172, 2022	42	2022
On the optimization landscape of neural collapse under mse loss: Global optimality with unconstrained features J Zhou, X Li, T Ding, C You, Q Qu, Z Zhu International Conference on Machine Learning, 27179-27202, 2022	41	2022
A nonconvex approach for exact and efficient multichannel sparse blind deconvolution Q Qu, X Li, Z Zhu Advances in Neural Information Processing Systems 32, 2019	41*	2019
Geometric analysis of nonconvex optimization landscapes for overcomplete learning Q Qu, Y Zhai, X Li, Y Zhang, Z Zhu International Conference on Learning Representations 2020, 2019	37*	2019
Short-and-Sparse Deconvolution--A Geometric Approach Y Lau, Q Qu, HW Kuo, P Zhou, Y Zhang, J Wright International Conference on Learning Representations 2020, 2019	29	2019
Robust zero‐point attraction least mean square algorithm on near sparse system identification J Jin, Q Qu, Y Gu IET Signal Processing 7 (3), 210-218, 2013	26	2013
Robust recovery via implicit bias of discrepant learning rates for double over-parameterization C You, Z Zhu, Q Qu, Y Ma Neural Information Processing Systems 2020, 2020	25	2020
Are all losses created equal: A neural collapse perspective J Zhou, C You, X Li, K Liu, S Liu, Q Qu, Z Zhu Advances in Neural Information Processing Systems 35, 31697-31710, 2022	17	2022

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