10 citations · 10 across the 1 of their papers we have counts for
3 papers
Lower Bounds for Adversarially Robust PAC Learning
Dimitrios I. Diochnos, Saeed Mahloujifar, Mohammad Mahmoody
In this work, we initiate a formal study of probably approximately correct (PAC) learning under evasion attacks, where the adversary's goal is to \emph{misclassify} the adversarial…
Adversarial Risk and Robustness: General Definitions and Implications for the Uniform Distribution
Dimitrios I. Diochnos, Saeed Mahloujifar, Mohammad Mahmoody
We study adversarial perturbations when the instances are uniformly distributed over . We study both "inherent" bounds that apply to any problem and any classifier for s…
The Curse of Concentration in Robust Learning: Evasion and Poisoning Attacks from Concentration of Measure
Saeed Mahloujifar, Dimitrios I. Diochnos, Mohammad Mahmoody
Many modern machine learning classifiers are shown to be vulnerable to adversarial perturbations of the instances. Despite a massive amount of work focusing on making classifiers r…