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[NeurIPS 2020] Rethinking the Value of Labels for Improving Class-Imbalanced Learning
Active Learning. The Secret of Training Models Without Labels.
IADF School 2022: Learning with Zero/Few Labels
Ep05: Semi‑Supervised Learning: Doing More With Less Labels
Learning To Classify Images Without Labels (Paper Explained)
Unit8 Talks #15 - On technology - Machine Learning with few labels
Leveraging single and cross-modal unlabeled data for learning with limited labels
Less Labelling: Active Learning with Possibility Theory
Ruohan Wang | Global labels and few-shot learning
Doing More With Less; Label-Efficient Learning for Euclid and Rubin
Bharath Hariharan - Visual Learning with fewer labels
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Last Updated: August 17, 2026
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![[NeurIPS 2020] Rethinking the Value of Labels for Improving Class-Imbalanced Learning](https://i.ytimg.com/vi/XltXZ3OZvyI/mqdefault.jpg)
