3 citations · 3 across the 5 of their papers we have counts for
5 papers
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…
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…
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…
Enhancing Adversarial Attacks: The Similar Target Method
Shuo Zhang, Ziruo Wang, Zikai Zhou +1
Deep neural networks are vulnerable to adversarial examples, posing a threat to the models' applications and raising security concerns. An intriguing property of adversarial exampl…
Why flatness does and does not correlate with generalization for deep neural networks
Shuofeng Zhang, Isaac Reid, Guillermo Valle Pérez +1
The intuition that local flatness of the loss landscape is correlated with better generalization for deep neural networks (DNNs) has been explored for decades, spawning many differ…