Optimizing Few-Shot Learning Based on Variational Autoencoders
Despite the importance of few-shot learning, the lack of labeled training data in the real world makes it extremely challenging for existing machine learning methods because this limited dataset does not well represent the data variance. In this research, we suggest employing a generative approach u...
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| Main Authors: | , |
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| Format: | article |
| Language: | EN |
| Published: |
MDPI AG
2021
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| Subjects: | |
| Online Access: | https://doaj.org/article/df412ec1c61f467f80127d304633eb2e |
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