3 papers
cs.CV2026
Why Not Hyperparameter-Friendly Optimisation? A Monotonic Adaptive Norm Rescaling Approach For Long-Tailed Recognition
Shuo Zhang, Chenqi Li, Tingting Zhu
Long-tailed recognition poses a significant challenge for deep learning. The two-stage decoupling paradigm, which separates representation learning from classifier retraining, offe…
cs.LG2026
Closed-form norm scaling with data for overparameterized linear regression and diagonal linear networks under bias
Shuofeng Zhang, Ard Louis
For overparameterized linear regression with isotropic Gaussian design and minimum- interpolator , we give a unified, high-probability characterization for the s…
cs.LG2026
Position: Many generalization measures for deep learning are fragile
Shuofeng Zhang, Ard Louis
In this position paper, we argue that many post-mortem generalization measures -- those computed on trained networks -- are \textbf{fragile}: small training modifications that bare…