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Cutting to the chase with warm-start contextual bandits., , , and . Knowl. Inf. Syst., 65 (9): 3533-3565 (September 2023)HMAB: Self-Driving Hierarchy of Bandits for Integrated Physical Database Design Tuning., , , and . Proc. VLDB Endow., 16 (2): 216-229 (2022)DBA bandits: Self-driving index tuning under ad-hoc, analytical workloads with safety guarantees., , , and . ICDE, page 600-611. IEEE, (2021)DBA bandits: Self-driving index tuning under ad-hoc, analytical workloads with safety guarantees., , , and . CoRR, (2020)No DBA? No regret! Multi-armed bandits for index tuning of analytical and HTAP workloads with provable guarantees., , , and . CoRR, (2021)A Note on Bounding Regret of the C$^2$UCB Contextual Combinatorial Bandit., , , and . CoRR, (2019)No DBA? No Regret! Multi-Armed Bandits for Index Tuning of Analytical and HTAP Workloads With Provable Guarantees., , , and . IEEE Trans. Knowl. Data Eng., 35 (12): 12855-12872 (December 2023)Cutting to the Chase with Warm-Start Contextual Bandits., , , and . ICDM, page 459-468. IEEE, (2021)Bandit Algorithms with Application to Database Index Selection.. University of Melbourne, Parkville, Victoria, Australia, (2023)base-search.net (ftumelbourne:oai:jupiter.its.unimelb.edu.au:11343/329697).