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Predicting Consumer Behavior in Commerce Search., , and . ICML, icml.cc / Omnipress, (2012)A Differentially Private Linear-Time fPTAS for the Minimum Enclosing Ball Problem., and . NeurIPS, (2022)Improved Spectral-Norm Bounds for Clustering., and . APPROX-RANDOM, volume 7408 of Lecture Notes in Computer Science, page 37-49. Springer, (2012)Differentially Private Contextual Linear Bandits., and . NeurIPS, page 4301-4311. (2018)Differentially Private Algorithms for Learning Mixtures of Separated Gaussians., , , and . NeurIPS, page 168-180. (2019)The power of synergy in differential privacy: Combining a small curator with local randomizers., , , , and . CoRR, (2019)Differentially Private Approximations of a Convex Hull in Low Dimensions., and . ITC, volume 199 of LIPIcs, page 18:1-18:16. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, (2021)The Power of Synergy in Differential Privacy: Combining a Small Curator with Local Randomizers., , , , and . ITC, volume 163 of LIPIcs, page 14:1-14:25. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, (2020)An Optimal Private Stochastic-MAB Algorithm based on Optimal Private Stopping Rule., and . ICML, volume 97 of Proceedings of Machine Learning Research, page 5579-5588. PMLR, (2019)On The Randomness Complexity of Property Testing., and . Comput. Complex., 19 (1): 99-133 (2010)