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Performance and Convergence of Multi-user Online Learning., и . GAMENETS, том 75 из Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, стр. 321-336. Springer, (2011)Discovering, Learning and Exploiting Relevance., и . NIPS, стр. 1233-1241. (2014)Explaining by Imitating: Understanding Decisions by Interpretable Policy Learning., , , и . ICLR, OpenReview.net, (2021)Group Retention when Using Machine Learning in Sequential Decision Making: the Interplay between User Dynamics and Fairness., , , и . NeurIPS, стр. 15243-15252. (2019)Vector Optimization with Stochastic Bandit Feedback., и . AISTATS, том 206 из Proceedings of Machine Learning Research, стр. 2165-2190. PMLR, (2023)A systematic learning method for optimal jamming., , , и . ICC, стр. 2822-2827. IEEE, (2015)Learning the Pareto Set Under Incomplete Preferences: Pure Exploration in Vector Bandits., , , и . AISTATS, том 238 из Proceedings of Machine Learning Research, стр. 3070-3078. PMLR, (2024)Contextual Online Learning for Multimedia Content Aggregation., и . IEEE Trans. Multim., 17 (4): 549-561 (2015)Online learning in decentralized multi-user spectrum access with synchronized explorations., и . MILCOM, стр. 1-6. IEEE, (2012)Learning traffic congestion by contextual bandit problems for optimum localization., , , и . SIU, стр. 1-4. IEEE, (2017)