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I'd also point out that people always focus on just the labelling savings from active learning but there are other benefits in practice too: 1) faster feedback
by razcle 6y ago
I'd also point out that people always focus on just the labelling savings from active learning but there are other benefits in practice too:
1) faster feedback on model performance during the annotation process
and 2) Better engagement from the annotators as they can see the benefit of their work.
- andy99 6y agoI'd add that there is a deep connection between active learning and understanding the "domain of expertise" of a model, for example what inputs are ambiguous or low confidence, and which are out of distribution. E.g. BALD is a form of out of distribution detection - a point with high disagreement it not only useful to add to the training pool, it is a point for which the current model has no business making a prediction.