A High Dimensional Model for Adversarial Training: Geometry and Trade-Offs

1 code implementation • 8 Feb 2024 • Kasimir Tanner, Matteo Vilucchio, Bruno Loureiro, Florent Krzakala

This work investigates adversarial training in the context of margin-based linear classifiers in the high-dimensional regime where the dimension $d$ and the number of data points $n$ diverge with a fixed ratio $\alpha = n / d$.

Adversarial Robustness