CRAB is a new active learning strategy that combines positive and negative label correlation matrices with beta scoring rules to improve multi-label text classification on imbalanced datasets.
A review of uncertainty quantification in deep learning: Techniques, applications and challenges
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Multi-Label Bayesian Active Learning with Inter-Label Relationships
CRAB is a new active learning strategy that combines positive and negative label correlation matrices with beta scoring rules to improve multi-label text classification on imbalanced datasets.