Provably Safeguarding a Classifier from OOD and Adversarial Samples: an Extreme Value Theory Approach

Fuente: arXiv

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Bibliographic Details
Main Authors:	Atienza, Nicolas, Labreuche, Christophe, Cohen, Johanne, Sebag, Michele
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
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Internet

https://arxiv.org/abs/2501.10202