Adversarial Neural Pruning with Latent Vulnerability Suppression

ICML 2020 Divyam MadaanJinwoo ShinSung Ju Hwang

Despite the remarkable performance of deep neural networks on various computer vision tasks, they are known to be susceptible to adversarial perturbations, which makes it challenging to deploy them in real-world safety-critical applications. In this paper, we conjecture that the leading cause of adversarial vulnerability is the distortion in the latent feature space, and provide methods to suppress them effectively... (read more)

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