2 papers
cs.LG2026
On the Width Scaling of Neural Optimizers Under Matrix Operator Norms I: Row/Column Normalization and Hyperparameter Transfer
Ruihan Xu, Jiajin Li, Yiping Lu
A central question in modern deep learning is how to design optimizers whose behavior remains stable as the network width increases. We address this question by interpreting se…
stat.ML2025
Benign overfitting in Fixed Dimension via Physics-Informed Learning with Smooth Inductive Bias
Honam Wong, Wendao Wu, Fanghui Liu +1
Recent advances in machine learning have inspired a surge of research into reconstructing specific quantities of interest from measurements that comply with certain physical laws.…