43 citations · 45 across the 4 of their papers we have counts for
4 papers
Transductive Robust Learning Guarantees
Omar Montasser, Steve Hanneke, Nathan Srebro
We study the problem of adversarially robust learning in the transductive setting. For classes of bounded VC dimension, we propose a simple transductive learner that…
Adversarially Robust Learning with Unknown Perturbation Sets
Omar Montasser, Steve Hanneke, Nathan Srebro
We study the problem of learning predictors that are robust to adversarial examples with respect to an unknown perturbation set, relying instead on interaction with an adversarial…
Reducing Adversarially Robust Learning to Non-Robust PAC Learning
Omar Montasser, Steve Hanneke, Nathan Srebro
We study the problem of reducing adversarially robust learning to standard PAC learning, i.e. the complexity of learning adversarially robust predictors using access to only a blac…
VC Classes are Adversarially Robustly Learnable, but Only Improperly
Omar Montasser, Steve Hanneke, Nathan Srebro
We study the question of learning an adversarially robust predictor. We show that any hypothesis class with finite VC dimension is robustly PAC learnable with an impr…