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Contextual Bandits with Continuous Actions: Smoothing, Zooming, and Adapting., , , and . J. Mach. Learn. Res., (2020)Multitask Bandit Learning through Heterogeneous Feedback Aggregation., , , , and . CoRR, (2020)Efficient Active Learning Halfspaces with Tsybakov Noise: A Non-convex Optimization Approach., and . CoRR, (2023)Hierarchical Unimodal Bandits., , and . ECML/PKDD (4), volume 13716 of Lecture Notes in Computer Science, page 269-283. Springer, (2022)Active Online Learning with Hidden Shifting Domains., , , and . AISTATS, volume 130 of Proceedings of Machine Learning Research, page 2053-2061. PMLR, (2021)Efficient active learning of sparse halfspaces with arbitrary bounded noise., , and . NeurIPS, (2020)Bandit Multiclass Linear Classification: Efficient Algorithms for the Separable Case., , , , , and . ICML, volume 97 of Proceedings of Machine Learning Research, page 624-633. PMLR, (2019)Kullback-Leibler Maillard Sampling for Multi-armed Bandits with Bounded Rewards., , and . CoRR, (2023)Attribute-Efficient Learning of Halfspaces with Malicious Noise: Near-Optimal Label Complexity and Noise Tolerance., and . ALT, volume 132 of Proceedings of Machine Learning Research, page 1072-1113. PMLR, (2021)Thompson Sampling for Robust Transfer in Multi-Task Bandits., , and . ICML, volume 162 of Proceedings of Machine Learning Research, page 23363-23416. PMLR, (2022)