Overcoming the convex barrier for simplex input
Recent progress in neural network verification has challenged the notion of a convex barrier, that is, an inherent weakness in the convex relaxation of the output of a neural network. Specifically, there now exists a tight relaxation for verifying the robustness of a neural network to `∞ input pertu...
| Principais autores: | , , , |
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| Formato: | Conference item |
| Idioma: | English |
| Publicado em: |
NeurIPS Proceedings
2021
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