Active Learning from Multiple Knowledge Sources

  title={Active Learning from Multiple Knowledge Sources},
  author={Yan Yan and R{\'o}mer Rosales and Glenn Fung and Faisal Farooq and R. Bharat Rao and Jennifer G. Dy},
Some supervised learning tasks do not fit the usual single annotator scenario. In these problems, ground-truth may not exist and multiple annotators are generally available. A few approaches have been proposed to address this learning problem. In this setting active learning (AL), the problem of optimally selecting unlabeled samples for labeling, offers new challenges and has received little attention. In multiple annotator AL, it is not sufficient to select a sample for labeling since, in… CONTINUE READING
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