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...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
ICLR
2021
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| Online Access: | https://hdl.handle.net/1721.1/130110 |