Please also see my Google Scholar Profile for updated publication

Preprints

Sheng Liu, Zhihui Zhu, Qing Qu, Chong You (2022). Robust Training under Label Noise by Over-parameterization. In Submission.
Preprint – PDF –  BibTex

Jinxin Zhou (equal), Xiao Li (equal), Tianyu Ding, Chong You, Qing Qu (equal), Zhihui Zhu (equal) (2022). On the Optimization Landscape of Neural Collapse under MSE Loss: Global Optimality with Unconstrained Features. In Submission.
Preprint – PDF –  BibTex

Lijun Ding (equal), Liwei Jiang (equal), Yudong Chen, Qing Qu, Zhihui Zhu (2021). Rank Overspecified Robust Matrix Recovery: Subgradient Method and Exact Recovery. In Submission.
Preprint – PDF –  BibTex

Zhihui Zhu (equal), Tianyu Ding (equal), Jinxin Zhou, Xiao Li, Chong You, Jeremias Sulam, Qing Qu (2021). A Geometric Analysis of Neural Collapse with Unconstrained Features. In Submission.
Preprint – PDF –  Slides –  BibTex

Sheng Liu (equal), Xiao Li (equal), Yuexiang Zhai, Chong You, Zhihui Zhu, Carlos Fernandez-Granda, Qing Qu (2021). Convolutional Normalization: Improving Deep Convolutional Network Robustness and Training. In Submission.
Preprint – PDF –  BibTex

Yuqian Zhang, Qing Qu, John Wright (2020). From Symmetry to Geometry: Tractable Nonconvex Problems. In Submission to Proceedings of IEEE.
Preprint – PDF –  Slides – BibTex

Qing Qu (equal), Zhihui Zhu (equal), Xiao Li, Manolis C. Tsakiris, John Wright, Rene Vidal (2020). Finding the Sparsest Vectors in a Subspace: Theory, Algorithms, and Applications. In Submission.
Preprint – PDF – Slides – BibTex

Qing Qu, Yuexiang Zhai, Xiao Li, Yuqian Zhang, Zhihui Zhu (2019). Analysis of the Optimization Landscapes for Overcomplete Representation Learning. In Submission. (ICLR’20, oral, top 1.9%).
Preprint – PDF – Slides – BibTex

Yenson Lau (equal), Qing Qu (equal), Han-wen Kuo, Pengcheng Zhou, Yuqian Zhang, John Wright (2019). Short-and-Sparse Deconvolution – A Geometric Approach. In Submission. (ICLR’20).
Preprint – PDF – Code – Poster – Slides – Website – BibTex

Journal Articles

Xiao Li (equal), Shixiang Chen (equal), Zengde Deng, Qing Qu, Zhihui Zhu, Anthony Man Cho So (2021). Weakly Convex Optimization over Stiefel Manifold Using Riemannian Subgradient-Type Methods. Accepted at SIAM Journal on Optimization.
Preprint – PDF – Code – BibTex

Qing Qu, Xiao Li, Zhihui Zhu (2019). Exact Recovery of Multichannel Sparse Blind Deconvolution via Gradient Descent. SIAM Journal on Imaging Science, 13(3): 1630–1652, 2020. (NeurIPS’19, spotlight, top 3%).
Preprint – PDF – Code – Poster – Slides – BibTex

Qing Qu, Yuqian Zhang, Yonina C. Eldar, John Wright (2019). Convolutional Phase Retrieval via Gradient Descent. IEEE Trans. on Information Theory, 66(3):1785–1821, Mar. 2020. (NeurIPS’17).
Preprint – PDF – Code – Poster – Slides – BibTex

Ju Sun, Qing Qu, John Wright (2018). A Geometric Analysis of Phase Retrieval. Foundations of Computational Mathematics, 18(5):1131–1198, 2018. (ISIT’16).
Preprint – PDF – Code – Slides – BibTex

Ju Sun, Qing Qu, John Wright (2017). Complete Dictionary Recovery over the Sphere I: Overview and the Geometric Picture. IEEE Trans. on Information Theory, 63(2): 853 – 884, Feb. 2017. (ICML’15).
Preprint – PDF – Code – Poster – BibTex

Ju Sun, Qing Qu, John Wright (2017). Complete Dictionary Recovery over the Sphere II: Recovery by Riemannian Trust-region Method. IEEE Trans. on Information Theory, 63(2): 853 – 884, Feb. 2017.
Preprint – PDF – Code – Poster – BibTex

Qing Qu, Ju Sun, John Wright (2016). Finding a Sparse Vector in a Subspace: Linear Sparsity Using Alternating Directions. IEEE Trans. on Information Theory, 62(10): 5855 – 5880, Oct. 2016 (NeurIPS’14).
Preprint – PDF – Code – Poster – Slides – BibTex

Qing Qu, Nasser M. Nasrabadi, Trac D. Tran (2015). Subspace Vertex Pursuit: A Fast and Robust Near-Separable Nonnegative Matrix Factorization Method for Hyperspectral Unmixing. IEEE Journal of Selected Topics in Signal Processing, 9(6): 1142 – 1155, Sept. 2015.
PDF – Poster – BibTex

Qing Qu, Nasser M. Nasrabadi, Trac D. Tran (2014). Abundance Estimation for Bilinear Mixture Models via Joint Sparse and Low-Rank Representation. IEEE Transactions on Geoscience and Remote Sensing, 52(7): 4404 – 4423, Jul. 2014.
PDF – Code – Poster – Slides – BibTex

Xiaoxia Sun, Qing Qu, Nasser M. Nasrabadi, Trac D. Tran (2014). Structured Priors for Sparse-Representation-Based Hyperspectral Image Classification. IEEE Geoscience and Remote Sensing Letters, 11(7): 1235 – 1239, Jul. 2014.
Preprint – PDF – BibTex

Jian Jin, Qing Qu, Yuantao Gu (2013). Robust Zero-point Attraction Least Mean Square Algorithm on Near Sparse System Identification. IET Signal Processing, 7(3): 210 – 218, May 2013.
Preprint – PDF – BibTex

Conference Papers

Zhihui Zhu (equal), Tianyu Ding (equal), Jinxin Zhou, Xiao Li, Chong You, Jeremias Sulam, Qing Qu (2021). A Geometric Analysis of Neural Collapse with Unconstrained Features. Neural Information Processing Systems (NeurIPS’21), 2021. (spotlight, top 3%)

Sheng Liu (equal), Xiao Li (equal), Yuexiang Zhai, Chong You, Zhihui Zhu, Carlos Fernandez-Granda, Qing Qu (2021). Convolutional Normalization: Improving Deep Convolutional Network Robustness and Training. Neural Information Processing Systems (NeurIPS’21), 2021.

Lijun Ding (equal), Liwei Jiang (equal), Yudong Chen, Qing Qu, Zhihui Zhu (2021). Rank Overspecified Robust Matrix Recovery: Subgradient Method and Exact Recovery. Neural Information Processing Systems (NeurIPS’21), 2021.

Chong You (equal), Zhihui Zhu (equal), Qing Qu, Yi Ma (2020). Robust Recovery via Implicit Bias of Discrepant Learning Rates for Double Over-parameterization. Neural Information Processing Systems (NeurIPS’20), 2020. (spotlight, top 4%)

Qing Qu, Yuexiang Zhai, Xiao Li, Yuqian Zhang, and Zhihui Zhu (2020). Geometric Analysis of Nonconvex Optimization Landscapes for Overcomplete Learning. International Conference on Learning Representations (ICLR’20), 2020. (oral, top 1.9%)

Yenson Lau (equal), Qing Qu (equal), Han-wen Kuo, Pengcheng Zhou, Yuqian Zhang, and John Wright (2020). Short and Sparse Deconvolution — A Geometric Approach. International Conference on Learning Representations (ICLR’20), 2020.

Qing Qu, Xiao Li, and Zhihui Zhu (2019). A Nonconvex Approach for Exact and Efficient Multichannel Sparse Blind Deconvolution. Neural Information Processing Systems (NeurIPS’19), 2019. (spotlight, top 3%)

Qing Qu, Xiao Li, and Zhihui Zhu (2019). Exact and Efficient Multi-Channel Sparse Blind Deconvolution — A Nonconvex Approach. Asilomar Conference on Signals, Systems, and Computers (ACSSC’19), 2019.

Qing Qu, Yuqian Zhang, Yonina Eldar, and John Wright (2017). Convolutional Phase Retrieval. Neural Information Processing Systems (NeurIPS’17), 2017.

Ju Sun, Qing Qu, and John Wright (2016). A Geometric Analysis of Phase Retrieval. IEEE International Symposium on Information Theory (ISIT’16), 2016.

Ju Sun, Qing Qu, and John Wright (2015). Complete Dictionary Recovery using Nonconvex Optimization. International Conference on Machine Learning (ICML’15), 2015.

Ju Sun, Qing Qu, and John Wright (2015). Complete Dictionary Recovery over the Sphere. International Conference on Sampling Theory and Applications (SampTA’15), 2015.

Qing Qu, Ju Sun, and John Wright (2014). Finding a Sparse Vector in a Subspace: Linear Sparsity using Alternating Directions. Neural Information Processing Systems (NeurIPS’14), 2014.

Qing Qu, Xiaoxia Sun, Nasser M. Nasrabadi, and Trac D. Tran (2014). Subspace Vertex Pursuit for Separable Non-negative Matrix Factorization in Hyperspectral Unmixing. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP’14), 2014.

Qing Qu, Nasser M. Nasrabadi, and Trac D. Tran (2013). Hyperspectral Abundance Estimation for the Generalized Bilinear Model with Joint Sparsity Constraint. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP’13), 2013.

Workshop Papers

Yenson Lau (equal), Qing Qu (equal), Han-wen Kuo, Pengcheng Zhou, Yuqian Zhang, and John Wright (2019). Short and Sparse Deconvolution — A Geometric Approach. In Workshop on Signal Processing with Adaptive Sparse Structured Representations (SPARS’19), 2019.

Qing Qu, Yuqian Zhang, Yonina Eldar, and John Wright (2017). Convolutional Phase Retrieval via Gradient Descent. In Workshop on Signal Processing with Adaptive Sparse Structured Representations (SPARS’17), 2017. (oral)

Ju Sun, Qing Qu, John Wright (2015). When Are Nonconvex Problems Not Scary?. NeurIPS’15 Workshop on Nonconvex Optimization for Machine Learning, 2015.

Ju Sun, Qing Qu, and John Wright (2015). Complete Dictionary Recovery over the Sphere. In Workshop on Signal Processing with Adaptive Sparse Structured Representations (SPARS’15), 2015. (oral, best student paper award)