Training for faster adversarial robustness verification via inducing Relu stability

We explore the concept of co-design in the context of neural network verification. Specifically, we aim to train deep neural networks that not only are robust to adversarial perturbations but also whose robustness can be verified more easily. To this end, we identify two properties of network models...

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Bibliographic Details
Main Authors: Xiao, Kai Yuanqing (Author), Tjeng, Vincent (Author), Shafiullah, Nur Muhammad Mahi (Author), Mądry, Aleksander (Author)
Other Authors: Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor)
Format: Article
Language:English
Published: ICLR, 2021-03-09T18:40:41Z.
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