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Active Learning for Non-Parametric Regression Using Purely Random Trees

Jack Goetz, Ambuj Tewari, Paul Zimmerman

Neural Information Processing Systems

Active learning is the task of using labelled data to select additional points to label, with the goal of fitting the most accurate model with a fixed budget of labelled points. In binary classification active learning is known to produce faster rates than passive learning for a broad range of settings.