Safety verification for deep neural networks with provable guarantees
Computing systems are becoming ever more complex, increasingly often incorporating deep learning components. Since deep learning is unstable with respect to adversarial perturbations, there is a need for rigorous software development methodologies that encompass machine learning. This paper describe...
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Leibniz International Proceedings in Informatics, LIPIcs
2019
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