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How to Compare Adversarial Robustness of Classifiers from a Global Perspective.

, , and . ICANN (1), volume 12891 of Lecture Notes in Computer Science, page 29-41. Springer, (2021)

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Interpretable Locally Adaptive Nearest Neighbors., , and . Neurocomputing, (2022)Interpretation of linear classifiers by means of feature relevance bounds., , , and . Neurocomputing, (2018)Robustness in Machine Learning: Adversarial Perturbations, Explanations & Intuition.. Bielefeld University, Germany, (2022)Intuitiveness in Active Teaching., , , , and . CoRR, (2020)Why robots should be technical: Correcting mental models through technical architecture concepts., , , , and . CoRR, (2020)Locally Adaptive Nearest Neighbors., , and . ESANN, page 667-672. (2020)Prototype-Based Online Learning on Homogeneously Labeled Streaming Data., , , and . ICANN (2), volume 12397 of Lecture Notes in Computer Science, page 204-213. Springer, (2020)Classification of motor errors to provide real-time feedback for sports coaching in virtual reality - A case study in squats and Tai Chi pushes., , , , and . Comput. Graph., (2018)Recovering Localized Adversarial Attacks., , and . ICANN (1), volume 11727 of Lecture Notes in Computer Science, page 302-311. Springer, (2019)How to Compare Adversarial Robustness of Classifiers from a Global Perspective., , and . ICANN (1), volume 12891 of Lecture Notes in Computer Science, page 29-41. Springer, (2021)