Intriguing generalization and simplicity of adversarially trained neural networks

16 Jun 2020Chirag AgarwalPeijie ChenAnh Nguyen

Adversarial training has been the topic of dozens of studies and a leading method for defending against adversarial attacks. Yet, it remains unknown (a) how adversarially-trained classifiers (a.k.a "robust" classifiers) generalize to new types of out-of-distribution examples; and (b) what hidden representations were learned by robust networks... (read more)

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