Machine Learning Department
School of Computer Science, Carnegie Mellon University


A Bound on the Label Complexity
of Agnostic Active Learning

Steve Hanneke

March 2007


Keywords: Agnostic active learning, label complexity, PAC

We study the label complexity of pool-based active learning in the agnostic PAC model. Specifically, we derive a general upper bound on the number of label requests made by the A2 algorithm proposed by Balcan et al. This represents the first nontrivial general-purpose upper bound on label complexity in the agnostic PAC model.

10 pages

SCS Technical Report Collection
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