arXiv stat.ML
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Generalization and Trade-off in Adversarial Training: An RKHS Perspective via Kernel Integral Operators
arXiv:2607.27995v1 Announce Type: new Abstract: Adversarial training has emerged as a powerful approach for protecting models against adversarial attacks in a broad range of real-world applications. In this paper, we study adversarial training in the reproducing kernel Hilbert space (RKHS) framework through the associa