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A fully adaptive algorithm for pure exploration in linear bandits.

, , and . AISTATS, volume 84 of Proceedings of Machine Learning Research, page 843-851. PMLR, (2018)

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Nearly Optimal Best-of-Both-Worlds Algorithms for Online Learning with Feedback Graphs., , and . NeurIPS, (2022)Tight upper bounds on the redundancy of optimal binary AIFV codes., , and . ISIT, page 6-10. IEEE, (2016)Worst-case Redundancy of Optimal Binary AIFV Codes and Their Extended Codes., , and . IEEE Trans. Inf. Theory, 63 (8): 5074-5086 (2017)Copeland Dueling Bandit Problem: Regret Lower Bound, Optimal Algorithm, and Computationally Efficient Algorithm., , and . ICML, volume 48 of JMLR Workshop and Conference Proceedings, page 1235-1244. JMLR.org, (2016)Variable-to-Fixed Length Homophonic Coding with a Modified Shannon-Fano-Elias Code., and . CoRR, (2016)Online Dense Subgraph Discovery via Blurred-Graph Feedback., , , and . ICML, volume 119 of Proceedings of Machine Learning Research, page 5522-5532. PMLR, (2020)Follow-the-Perturbed-Leader with Fréchet-type Tail Distributions: Optimality in Adversarial Bandits and Best-of-Both-Worlds., , , and . CoRR, (2024)Fast Linear-Programming decoding of LDPC codes over GF(2m)., and . ISITA, page 754-758. IEEE, (2012)Multi-Player Approaches for Dueling Bandits., , and . CoRR, (2024)Optimal Regret Analysis of Thompson Sampling in Stochastic Multi-armed Bandit Problem with Multiple Plays., , and . ICML, volume 37 of JMLR Workshop and Conference Proceedings, page 1152-1161. JMLR.org, (2015)