Theoretical Robustness Bounds on the Successful Adversarial Examples in Probabilistic Models: Comprehensive Insights From Gaussian Processes
An adversarial example (AE) is an attack method targeting machine learning, which is crafted by adding an imperceptible perturbation to input data to induce misclassification. In the present paper, we investigate the upper bound of the probability of successful AE attack under Gaussian Process (GP)...
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| Autori principali: | , |
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| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
IEEE
2026-01-01
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| Serie: | IEEE Access |
| Soggetti: | |
| Accesso online: | https://ieeexplore.ieee.org/document/11568753/ |
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