90 citations · 120 across the 9 of their papers we have counts for
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cs.LG2019★ 90 cited
Adversarial Policies: Attacking Deep Reinforcement Learning
Adam Gleave, Michael Dennis, Cody Wild +3
Deep reinforcement learning (RL) policies are known to be vulnerable to adversarial perturbations to their observations, similar to adversarial examples for classifiers. However, a…
cs.CR2019★ 8 cited
ALOHA: Auxiliary Loss Optimization for Hypothesis Augmentation
Ethan M. Rudd, Felipe N. Ducau, Cody Wild +2
Malware detection is a popular application of Machine Learning for Information Security (ML-Sec), in which an ML classifier is trained to predict whether a given file is malware or…