Towards Anytime Active Learning : Interrupting Experts to Reduce Annotation Costs

  • Maria E. Ramirez-Loaiza mramire, Aron Culotta aculotta, Mustafa Bilgic mbilgic
  • Published 2013
Many active learning methods use annotation cost or expert quality as part of their framework to select the best data for annotation. While these methods model expert quality, availability, or expertise, they have no direct influence on any of these elements. We present a novel framework built upon decision-theoretic active learning that allows the learner… (More)