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Online allocation and homogeneous partitioning for piecewise constant mean-approximation., and . NIPS, page 1970-1978. (2012)Finite Time Analysis of Stratified Sampling for Monte Carlo., and . NIPS, page 1278-1286. (2011)Tight (Lower) Bounds for the Fixed Budget Best Arm Identification Bandit Problem., and . COLT, volume 49 of JMLR Workshop and Conference Proceedings, page 590-604. JMLR.org, (2016)Sparse Recovery with Brownian Sensing., , and . NIPS, page 1782-1790. (2011)Adaptive strategy for stratified Monte Carlo sampling., , and . J. Mach. Learn. Res., (2015)A minimax near-optimal algorithm for adaptive rejection sampling., , , and . CoRR, (2018)Local minimax rates for closeness testing of discrete distributions., , and . CoRR, (2019)Upper-Confidence-Bound Algorithms for Active Learning in Multi-armed Bandits., , , , and . ALT, volume 6925 of Lecture Notes in Computer Science, page 189-203. Springer, (2011)Adaptivity to Smoothness in X-armed bandits., and . COLT, volume 75 of Proceedings of Machine Learning Research, page 1463-1492. PMLR, (2018)Bandit Theory meets Compressed Sensing for high dimensional Stochastic Linear Bandit., and . AISTATS, volume 22 of JMLR Proceedings, page 190-198. JMLR.org, (2012)