121 citations · 289 across the 19 of their papers we have counts for
3 papers · 1 filter
Robustness via curvature regularization, and vice versa
Seyed-Mohsen Moosavi-Dezfooli, Alhussein Fawzi, Jonathan Uesato +1
State-of-the-art classifiers have been shown to be largely vulnerable to adversarial perturbations. One of the most effective strategies to improve robustness is adversarial traini…
SparseFool: a few pixels make a big difference
Apostolos Modas, Seyed-Mohsen Moosavi-Dezfooli, Pascal Frossard
Deep Neural Networks have achieved extraordinary results on image classification tasks, but have been shown to be vulnerable to attacks with carefully crafted perturbations of the…
Divide, Denoise, and Defend against Adversarial Attacks
Seyed-Mohsen Moosavi-Dezfooli, Ashish Shrivastava, Oncel Tuzel
Deep neural networks, although shown to be a successful class of machine learning algorithms, are known to be extremely unstable to adversarial perturbations. Improving the robustn…