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Time-Accuracy Tradeoffs in Kernel Prediction: Controlling Prediction Quality.

, and . J. Mach. Learn. Res., (2017)

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An Adaptive Strategy for Active Learning with Smooth Decision Boundary., , and . ALT, volume 83 of Proceedings of Machine Learning Research, page 547-571. PMLR, (2018)Tight Rates in Supervised Outlier Transfer Learning., and . CoRR, (2023)Tracking Most Significant Arm Switches in Bandits., and . COLT, volume 178 of Proceedings of Machine Learning Research, page 2160-2182. PMLR, (2022)Adaptivity to Local Smoothness and Dimension in Kernel Regression., and . NIPS, page 3075-3083. (2013)Time-Accuracy Tradeoffs in Kernel Prediction: Controlling Prediction Quality., and . J. Mach. Learn. Res., (2017)Achieving the time of 1-NN, but the accuracy of k-NN., and . AISTATS, volume 84 of Proceedings of Machine Learning Research, page 1628-1636. PMLR, (2018)Quickshift++: Provably Good Initializations for Sample-Based Mean Shift., , and . ICML, volume 80 of Proceedings of Machine Learning Research, page 2299-2308. PMLR, (2018)Self-Tuning Bandits over Unknown Covariate-Shifts., and . ALT, volume 132 of Proceedings of Machine Learning Research, page 1114-1156. PMLR, (2021)The curse of dimension in nonparametric regression.. University of California, San Diego, USA, (2010)Nuances in Margin Conditions Determine Gains in Active Learning., , and . AISTATS, volume 151 of Proceedings of Machine Learning Research, page 8112-8126. PMLR, (2022)