Robustness evaluation of deep neural networks with provable guarantees
<p>This thesis presents methodologies to guarantee the robustness of deep neural networks, thus facilitating the deployment of deep learning techniques in safety-critical real-world systems. We study the maximum safe radius of a network with respect to an input, such that all the points within...
Главный автор: | |
---|---|
Другие авторы: | |
Формат: | Диссертация |
Язык: | English |
Опубликовано: |
2020
|
Предметы: |