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Black-box Attacks on Deep Neural Networks via Gradient Estimation., , , and . ICLR (Workshop), OpenReview.net, (2018)Lower Bounds on Cross-Entropy Loss in the Presence of Test-time Adversaries., , , and . ICML, volume 139 of Proceedings of Machine Learning Research, page 863-873. PMLR, (2021)Characterizing the Optimal 0-1 Loss for Multi-class Classification with a Test-time Attacker., , , , , , and . CoRR, (2023)LEAF: Navigating Concept Drift in Cellular Networks., , , , , , , and . PACMNET, 1 (CoNEXT2): 7:1-7:24 (2023)PAC-learning in the presence of evasion adversaries., , and . CoRR, (2018)Poison Forensics: Traceback of Data Poisoning Attacks in Neural Networks., , , and . USENIX Security Symposium, page 3575-3592. USENIX Association, (2022)Patch-based Defenses against Web Fingerprinting Attacks., , , and . AISec@CCS, page 97-109. ACM, (2021)Analyzing the Robustness of Open-World Machine Learning., , , , , , and . AISec@CCS, page 105-116. ACM, (2019)Backdoor Attacks Against Deep Learning Systems in the Physical World., , , , , and . CVPR, page 6206-6215. Computer Vision Foundation / IEEE, (2021)Enhancing robustness of machine learning systems via data transformations., , , and . CISS, page 1-5. IEEE, (2018)