Adversarially Robust PAC Learning with Optimal VC Rates
arXiv:2609.24260v1 Announce Type: new Abstract: We study the problem of \emph{adversarially robust} PAC learning. In this framework, the learner observes independent samples from an unknown distribution over $\mathcal{X} \times \{0,1\}$, as in classical PAC learning. However, given a perturbation m…
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- 2026-09-22 04:00 · arXiv stat.ML
Adversarially Robust PAC Learning with Optimal VC Rates