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Adversarially Robust Streaming Algorithms via Differential Privacy., , , , и . J. ACM, 69 (6): 42:1-42:14 (2022)Lower Bounds for Differential Privacy Under Continual Observation and Online Threshold Queries., , , , и . CoRR, (2024)Tricking the Hashing Trick: A Tight Lower Bound on the Robustness of CountSketch to Adaptive Inputs., , , и . AAAI, стр. 7235-7243. AAAI Press, (2023)On the Sample Complexity of Privately Learning Axis-Aligned Rectangles., и . NeurIPS, стр. 28286-28297. (2021)Private k-Means Clustering with Stability Assumptions., , и . AISTATS, том 108 из Proceedings of Machine Learning Research, стр. 2518-2528. PMLR, (2020)Closure Properties for Private Classification and Online Prediction., , , и . COLT, том 125 из Proceedings of Machine Learning Research, стр. 119-152. PMLR, (2020)Concentration Bounds for High Sensitivity Functions Through Differential Privacy., и . J. Priv. Confidentiality, (2019)Adaptive Data Analysis in a Balanced Adversarial Model., , и . CoRR, (2023)Clustering Algorithms for the Centralized and Local Models., и . ALT, том 83 из Proceedings of Machine Learning Research, стр. 619-653. PMLR, (2018)Differentially Private Approximate Quantiles., , и . ICML, том 162 из Proceedings of Machine Learning Research, стр. 10751-10761. PMLR, (2022)