Selecting Influential Examples: Active Learning with Expected Model Output Changes

@inproceedings{Freytag2014SelectingIE,
  title={Selecting Influential Examples: Active Learning with Expected Model Output Changes},
  author={Alexander Freytag and Erik Rodner and Joachim Denzler},
  booktitle={ECCV},
  year={2014}
}
In this paper, we introduce a new general strategy for active learning. The key idea of our approach is to measure the expected change of model outputs, a concept that generalizes previous methods based on expected model change and incorporates the underlying data distribution. For each example of an unlabeled set, the expected change of model predictions is calculated and marginalized over the unknown label. This results in a score for each unlabeled example that can be used for active… CONTINUE READING
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