Lightweight Lipschitz Margin Training for Certified Defense against Adversarial Examples

Hajime Ono, Tsubasa Takahashi, Kazuya Kakizaki

How can we make machine learning provably robust against adversarial examples in a scalable way? Since certified defense methods, which ensure $\epsilon$-robust, consume huge resources, t…