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On the (Un-)Avoidability of Adversarial Examples., and . CoRR, (2021)Identifying regions of trusted predictions., , , and . UAI, volume 161 of Proceedings of Machine Learning Research, page 2125-2134. AUAI Press, (2021)On Learnability wih Computable Learners., , , , and . ALT, volume 117 of Proceedings of Machine Learning Research, page 48-60. PMLR, (2020)Active Nearest-Neighbor Learning in Metric Spaces., , and . J. Mach. Learn. Res., (2017)Robustness Should Not Be at Odds with Accuracy., and . FORC, volume 218 of LIPIcs, page 5:1-5:20. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, (2022)Learning Losses for Strategic Classification., and . AAAI, page 7337-7344. AAAI Press, (2022)Adversarially Robust Learning with Tolerance., , and . ALT, volume 201 of Proceedings of Machine Learning Research, page 115-135. PMLR, (2023)Open Problem: Are all VC-classes CPAC learnable?, , , , and . COLT, volume 134 of Proceedings of Machine Learning Research, page 4636-4641. PMLR, (2021)Strategic Classification with Unknown User Manipulations., , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 18714-18732. PMLR, (2023)Adversarially Robust Learning with Tolerance., , and . CoRR, (2022)