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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...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2021
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8618453/ https://www.ncbi.nlm.nih.gov/pubmed/34828088 http://dx.doi.org/10.3390/e23111390 |