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Recent Deep Semi-supervised Learning Approaches and Related Works. (arXiv:2106.11528v2 [cs.LG] UPDATED)
July 6, 2022, 1:10 a.m. | Gyeongho Kim
cs.LG updates on arXiv.org arxiv.org
The author of this work proposes an overview of the recent semi-supervised
learning approaches and related works. Despite the remarkable success of neural
networks in various applications, there exist few formidable constraints
including the need for a large amount of labeled data. Therefore,
semi-supervised learning, which is a learning scheme in which the scarce labels
and a larger amount of unlabeled data are utilized to train models (e.g., deep
neural networks) is getting more important. Based on the key assumptions …
arxiv learning lg semi-supervised semi-supervised learning supervised learning
More from arxiv.org / cs.LG updates on arXiv.org
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