Self-Calibration and Biconvex Compressive Sensing. - Shuyang Ling; Thomas Strohmer (CoRR, 2015)

Simultaneous blind deconvolution and blind demixing via convex programming. - Shuyang Ling; Thomas Strohmer (ACSSC, 2016)

Rapid, Robust, and Reliable Blind Deconvolution via Nonconvex Optimization. - Xiaodong Li; Shuyang Ling; Thomas Strohmer; Ke Wei (CoRR, 2016)

Self-Calibration via Linear Least Squares. - Shuyang Ling; Thomas Strohmer (CoRR, 2016)

Regularized Gradient Descent: A Nonconvex Recipe for Fast Joint Blind Deconvolution and Demixing. - Shuyang Ling; Thomas Strohmer (CoRR, 2017)

Blind Deconvolution Meets Blind Demixing: Algorithms and Performance Bounds. - Shuyang Ling; Thomas Strohmer (IEEE Trans. Inf. Theory, 2017)

Self-Calibration and Bilinear Inverse Problems via Linear Least Squares. - Shuyang Ling; Thomas Strohmer (SIAM J. Imaging Sci., 2018)

On the Landscape of Synchronization Networks: A Perspective from Nonconvex Optimization. - Shuyang Ling; Ruitu Xu; Afonso S. Bandeira (SIAM J. Optim., 2019)

Near-Optimal Performance Bounds for Orthogonal and Permutation Group Synchronization via Spectral Methods. - Shuyang Ling (CoRR, 2020)

Certifying Global Optimality of Graph Cuts via Semidefinite Relaxation: A Performance Guarantee for Spectral Clustering. - Shuyang Ling; Thomas Strohmer (Found. Comput. Math., 2020)

When do birds of a feather flock together? k-Means, proximity, and conic programming. - Xiaodong Li; Yang Li; Shuyang Ling; Thomas Strohmer; Ke Wei (Math. Program., 2020)

Generalized Power Method for Generalized Orthogonal Procrustes Problem: Global Convergence and Optimization Landscape Analysis. - Shuyang Ling (CoRR, 2021)

Near-Optimal Bounds for Generalized Orthogonal Procrustes Problem via Generalized Power Method. - Shuyang Ling (CoRR, 2021)

Strong Consistency, Graph Laplacians, and the Stochastic Block Model. - Shaofeng Deng; Shuyang Ling; Thomas Strohmer (J. Mach. Learn. Res., 2021)

Improved Performance Guarantees for Orthogonal Group Synchronization via Generalized Power Method. - Shuyang Ling (SIAM J. Optim., 2022)

Improved theoretical guarantee for rank aggregation via spectral method. - Ziliang Samuel Zhong; Shuyang Ling (CoRR, 2023)

Local Geometry Determines Global Landscape in Low-rank Factorization for Synchronization. - Shuyang Ling (CoRR, 2023)

Solving orthogonal group synchronization via convex and low-rank optimization: tightness and landscape analysis. - Shuyang Ling (Math. Program., 2023)

Cross Entropy versus Label Smoothing: A Neural Collapse Perspective. - Li Guo; Keith W. Ross; Zifan Zhao; George Andriopoulos; Shuyang Ling; Yufeng Xu; Zixuan Dong (CoRR, 2024)

On the Exactness of SDP Relaxation for Quadratic Assignment Problem. - Shuyang Ling (CoRR, 2024)

Uncertainty Quantification of Spectral Estimator and MLE for Orthogonal Group Synchronization. - Ziliang Samuel Zhong; Shuyang Ling (CoRR, 2024)

Beyond Unconstrained Features: Neural Collapse for Shallow Neural Networks with General Data. - Wanli Hong; Shuyang Ling (CoRR, 2024)

Neural Collapse for Unconstrained Feature Model under Cross-entropy Loss with Imbalanced Data. - Wanli Hong; Shuyang Ling (J. Mach. Learn. Res., 2024)

Generalized Orthogonal Procrustes Problem under Arbitrary Adversaries. - Shuyang Ling (SIAM J. Matrix Anal. Appl., 2025)

Cross Entropy versus Label Smoothing: A Neural Collapse Perspective. - Li Guo; George Andriopoulos; Zifan Zhao; Zixuan Dong; Shuyang Ling; Keith W. Ross (Trans. Mach. Learn. Res., 2025)