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...
| 第一著者: | |
|---|---|
| その他の著者: | |
| フォーマット: | 学位論文 |
| 言語: | English |
| 出版事項: |
2020
|
| 主題: |