Weighted Optimization: better generalization by smoother interpolation. - Yuege Xie; Rachel A. Ward; Holger Rauhut; Hung-Hsu Chou (CoRR, 2020)

Gradient Descent for Deep Matrix Factorization: Dynamics and Implicit Bias towards Low Rank. - Hung-Hsu Chou; Carsten Gieshoff; Johannes Maly; Holger Rauhut (CoRR, 2020)

Accuracy, Efficiency and Optimization of Signal Fragmentation. - Russel Caflisch; Hung-Hsu Chou; Jonathan W. Siegel (Multiscale Model. Simul., 2020)

More is Less: Inducing Sparsity via Overparameterization. - Hung-Hsu Chou; Johannes Maly; Holger Rauhut (CoRR, 2021)

Non-negative Least Squares via Overparametrization. - Hung-Hsu Chou; Johannes Maly; Claudio Mayrink Verdun (CoRR, 2022)

Overparameterization and Generalization Error: Weighted Trigonometric Interpolation. - Yuege Xie; Hung-Hsu Chou; Holger Rauhut; Rachel A. Ward (SIAM J. Math. Data Sci., 2022)

Neural (Tangent Kernel) Collapse. - Mariia Seleznova; Dana Weitzner; Raja Giryes; Gitta Kutyniok; Hung-Hsu Chou (NeurIPS, 2023)

Robust Implicit Regularization via Weight Normalization. - Hung-Hsu Chou; Holger Rauhut; Rachel A. Ward (CoRR, 2023)

How to induce regularization in generalized linear models: A guide to reparametrizing gradient flow. - Hung-Hsu Chou; Johannes Maly; Dominik Stöger (CoRR, 2023)

Get rid of your constraints and reparametrize: A study in NNLS and implicit bias. - Hung-Hsu Chou; Johannes Maly; Claudio Mayrink Verdun; Bernardo Freitas Paulo da Costa; Heudson Mirandola (AISTATS, 2025)

GradPCA: Leveraging NTK Alignment for Reliable Out-of-Distribution Detection. - Mariia Seleznova; Hung-Hsu Chou; Claudio Mayrink Verdun; Gitta Kutyniok (CoRR, 2025)

Conflicting Biases at the Edge of Stability: Norm versus Sharpness Regularization. - Vít Fojtík; Maria Matveev; Hung-Hsu Chou; Gitta Kutyniok; Johannes Maly (CoRR, 2025)

Fast One-Pass Sparse Approximation of the Top Eigenvectors of Huge Low-Rank Matrices? Yes, MAM*! - Edem Boahen; Simone Brugiapaglia; Hung-Hsu Chou; Mark A. Iwen; Felix Krahmer (CoRR, 2025)