2021
DOI: 10.48550/arxiv.2112.02705
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Beyond Robustness: Resilience Verification of Tree-Based Classifiers

Abstract: 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 the model does not… Show more

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