2 papers
stat.ML2025
Kernel Learning with Adversarial Features: Numerical Efficiency and Adaptive Regularization
Antônio H. Ribeiro, David Vävinggren, Dave Zachariah +2
Adversarial training has emerged as a key technique to enhance model robustness against adversarial input perturbations. Many of the existing methods rely on computationally expens…
stat.ML2024
Efficient Optimization Algorithms for Linear Adversarial Training
Antônio H. RIbeiro, Thomas B. Schön, Dave Zahariah +1
Adversarial training can be used to learn models that are robust against perturbations. For linear models, it can be formulated as a convex optimization problem. Compared to method…