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Diameter-based Interactive Structure Search

International Conference on Artificial Intelligence and Statistics (AISTATS), 2019
Abstract

In this work, we introduce \emph{interactive structure search}, a generic framework that encompasses many interactive learning settings, both explored and unexplored. We show that a recently developed active learning algorithm of~\citet{TD17} can be adapted for interactive structure search, that it can be made noise-tolerant, and that it enjoys favorable convergence rates.

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