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The Ethereal
Self Meta Pseudo Labels: Meta Pseudo Labels Without The Teacher
December 27, 2022 ยท Declared Dead ยท ๐ International Conference on Machine Learning and Applications
"No code URL or promise found in abstract"
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Authors
Kei-Sing Ng, Qingchen Wang
arXiv ID
2212.13420
Category
cs.LG: Machine Learning
Cross-listed
cs.AI
Citations
1
Venue
International Conference on Machine Learning and Applications
Last Checked
4 months ago
Abstract
We present Self Meta Pseudo Labels, a novel semi-supervised learning method similar to Meta Pseudo Labels but without the teacher model. We introduce a novel way to use a single model for both generating pseudo labels and classification, allowing us to store only one model in memory instead of two. Our method attains similar performance to the Meta Pseudo Labels method while drastically reducing memory usage.
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