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Online Learning in Markov Decision Processes with Changing Cost Sequences., , and . ICML, volume 32 of JMLR Workshop and Conference Proceedings, page 512-520. JMLR.org, (2014)Learning piecewise Lipschitz functions in changing environments., , and . AISTATS, volume 108 of Proceedings of Machine Learning Research, page 3567-3577. PMLR, (2020)Measuring Re-identification Risk., , , , , , , , , and 1 other author(s). Proc. ACM Manag. Data, 1 (2): 149:1-149:26 (2023)Envy-Free Classification., , , and . NeurIPS, page 1238-1248. (2019)Semi-bandit Optimization in the Dispersed Setting., , and . UAI, volume 124 of Proceedings of Machine Learning Research, page 909-918. AUAI Press, (2020)How much data is sufficient to learn high-performing algorithms? generalization guarantees for data-driven algorithm design., , , , , and . STOC, page 919-932. ACM, (2021)SEPO: Selecting by pointing as an intuitive human-robot command interface., , , , , and . ICRA, page 1166-1171. IEEE, (2013)Data Driven Resource Allocation for Distributed Learning., , , , , and . AAAI Workshops, volume WS-17 of AAAI Technical Report, AAAI Press, (2017)Learning-augmented private algorithms for multiple quantile release., , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 16344-16376. PMLR, (2023)Dispersion for Data-Driven Algorithm Design, Online Learning, and Private Optimization., , and . FOCS, page 603-614. IEEE Computer Society, (2018)