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From Bandits to Experts: A Tale of Domination and Independence., , , and . NIPS, page 1610-1618. (2013)A Near-Optimal Best-of-Both-Worlds Algorithm for Online Learning with Feedback Graphs., , , and . NeurIPS, (2022)A New Theoretical Framework for Fast and Accurate Online Decision-Making., , , and . NeurIPS, page 9152-9166. (2021)Active Learning on Trees and Graphs., , , and . COLT, page 320-332. Omnipress, (2010)A Linear Time Active Learning Algorithm for Link Classification., , , and . NIPS, page 1619-1627. (2012)Worst-Case Analysis of Selective Sampling for Linear-Threshold Algorithms., , and . NIPS, page 241-248. (2004)A Last Switch Dependent Analysis of Satiation and Seasonality in Bandits., , , and . AISTATS, volume 151 of Proceedings of Machine Learning Research, page 971-990. PMLR, (2022)Learning the Stackelberg Equilibrium in a Newsvendor Game., , , , and . AAMAS, page 242-250. ACM, (2023)Trading-Off Payments and Accuracy in Online Classification with Paid Stochastic Experts., , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 34809-34830. PMLR, (2023)Stochastic Bandits with Delay-Dependent Payoffs., and . AISTATS, volume 108 of Proceedings of Machine Learning Research, page 1168-1177. PMLR, (2020)