Adversarial robustness guarantees for classification with Gaussian Processes
We investigate adversarial robustness of Gaussian Process classification (GPC) models. Specifically, given a compact subset of the input space T⊆ℝd enclosing a test point x∗ and a GPC trained on a dataset , we aim to compute the minimum and the maximum classification probability for the GPC over al...
| 主要な著者: | , , , , , |
|---|---|
| フォーマット: | Conference item |
| 言語: | English |
| 出版事項: |
Proceedings of Machine Learning Research
2020
|