Selective Self-Training for semi-supervised Learning

ICLR 2019 Jisoo JeongSeungeui LeeNojun Kwak

Semi-supervised learning (SSL) is a study that efficiently exploits a large amount of unlabeled data to improve performance in conditions of limited labeled data. Most of the conventional SSL methods assume that the classes of unlabeled data are included in the set of classes of labeled data... (read more)

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