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Unsupervised Few-Shot Feature Learning via Self-Supervised Training
Learning from limited exemplars (few-shot learning) is a fundamental, unsolved problem that has been laboriously explored in the machine learning community. However, current few-shot learners are mostly supervised and rely heavily on a large amount of labeled examples. Unsupervised learning is a mor...
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| Publicado no: | Front Comput Neurosci |
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| Main Authors: | , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Frontiers Media S.A.
2020
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7592391/ https://ncbi.nlm.nih.gov/pubmed/33178000 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fncom.2020.00083 |
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