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cs.LG2019
Robustness Certificates for Sparse Adversarial Attacks by Randomized Ablation
Alexander Levine, Soheil Feizi
Recently, techniques have been developed to provably guarantee the robustness of a classifier to adversarial perturbations of bounded L_1 and L_2 magnitudes by using randomized smo…
cs.LG2019★ 16 cited
Wasserstein Smoothing: Certified Robustness against Wasserstein Adversarial Attacks
Alexander Levine, Soheil Feizi
In the last couple of years, several adversarial attack methods based on different threat models have been proposed for the image classification problem. Most existing defenses con…
cs.LG2019★ 16 cited
Certifiably Robust Interpretation in Deep Learning
Alexander Levine, Sahil Singla, Soheil Feizi
Deep learning interpretation is essential to explain the reasoning behind model predictions. Understanding the robustness of interpretation methods is important especially in sensi…