Bayesian active learning using arbitrary binary valued queries

Authors:
Liu Yang;Steve Hanneke;Jaime Carbonell
Affiliations:
Machine Learning Department, Carnegie Mellon University;Department of Statistics, Carnegie Mellon University;Language Technologies Institute, Carnegie Mellon University
Venue:
ALT'10 Proceedings of the 21st international conference on Algorithmic learning theory
Year:
2010

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Abstract

We explore a general Bayesian active learning setting, in which the learner can ask arbitrary yes/no questions. We derive upper and lower bounds on the expected number of queries required to achieve a specified expected risk.