Global robustness evaluation of deep neural networks with provable guarantees for the Hamming distance
Deployment of deep neural networks (DNNs) in safety-critical systems requires provable guarantees for their correct behaviours. We compute the maximal radius of a safe norm ball around a given input, within which there are no adversarial examples for a trained DNN. We define global robustness as an...
| Autors principals: | , , , , , |
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| Format: | Conference item |
| Publicat: |
International Joint Conferences on Artificial Intelligence Organization
2019
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