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Learning under p-tampering poisoning attacks., , and . Ann. Math. Artif. Intell., 88 (7): 759-792 (2020)Effectively Using Public Data in Privacy Preserving Machine Learning., , , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 25718-25732. PMLR, (2023)Lower Bounds for Adversarially Robust PAC Learning., , and . ISAIM, (2020)Polynomial-Time Targeted Attacks on Coin Tossing for Any Number of Corruptions., , , and . TCC (2), volume 13043 of Lecture Notes in Computer Science, page 718-750. Springer, (2021)Property Inference from Poisoning., , and . IACR Cryptol. ePrint Arch., (2021)DP-RAFT: A Differentially Private Recipe for Accelerated Fine-Tuning., , , , and . CoRR, (2022)Computational Concentration of Measure: Optimal Bounds, Reductions, and More., , and . CoRR, (2019)NeuraCrypt is not private., , , , , and . CoRR, (2021)Renyi Differential Privacy of Propose-Test-Release and Applications to Private and Robust Machine Learning., , , , and . NeurIPS, (2022)SparseFed: Mitigating Model Poisoning Attacks in Federated Learning with Sparsification., , , , and . CoRR, (2021)