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Information and Technology, Technical University of Munich, Munich Center for Machine Learning
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Challenging the conventional wisdom that strong certified robustness requires heavy partitioning, this work shows how white-box knowledge of base classifiers in partition-aggregation ensembles can yield significantly tighter robustness guarantees against label-flipping attacks with fewer partitions.
