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Found 3 papers, 1 papers with code
Finding Dynamics Preserving Adversarial Winning Tickets
Modern deep neural networks (DNNs) are vulnerable to adversarial attacks and adversarial training has been shown to be a promising method for improving the adversarial robustness of DNNs.
Revisiting Parameter Sharing for Automatic Neural Channel Number Search
Nevertheless, it is unclear how parameter sharing affects the searching process.
Understanding and Quantifying Adversarial Examples Existence in Linear Classification
We show that linear classifiers can be made robust to strong adversarial examples attack in cases where no adversarial robust linear classifiers exist under the previous definition.
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