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Beyond Robustness: Resilience Verification of Tree-Based Classifiers
[article]
2021
arXiv
pre-print
In this paper we criticize the robustness measure traditionally employed to assess the performance of machine learning models deployed in adversarial settings. To mitigate the limitations of robustness, we introduce a new measure called resilience and we focus on its verification. In particular, we discuss how resilience can be verified by combining a traditional robustness verification technique with a data-independent stability analysis, which identifies a subset of the feature space where
arXiv:2112.02705v1
fatcat:ahw6lbkf7fbnnlubo7z5zuq4wy