Comparar métodos
Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.
| Aprendizagem por Transferência Online× | Aprendizagem por Transferência× | |
|---|---|---|
| Área | Aprendizado de máquina | Aprendizado de máquina |
| Família | Machine learning | Machine learning |
| Ano de origem≠ | 2010 | 2010 (formalized); 1990s (early roots) |
| Autor original≠ | Zhao, P. & Hoi, S. C. H. | Pan, S. J. & Yang, Q. (survey); Bengio, Y. (deep learning framing) |
| Tipo≠ | Online learning with source-domain knowledge transfer | Learning paradigm |
| Fonte seminal≠ | Zhao, P., & Hoi, S. C. H. (2010). OTL: A Framework of Online Transfer Learning. In Proceedings of the 27th International Conference on Machine Learning (ICML 2010), pp. 1231–1238. Omnipress. link ↗ | Pan, S. J., & Yang, Q. (2010). A Survey on Transfer Learning. IEEE Transactions on Knowledge and Data Engineering, 22(10), 1345–1359. DOI ↗ |
| Outros nomes | OTL, streaming transfer learning, incremental transfer learning, online domain adaptation | TL, domain adaptation, fine-tuning, pre-trained model adaptation |
| Relacionados≠ | 4 | 3 |
| Resumo≠ | Online Transfer Learning (OTL) extends transfer learning to sequential, streaming settings: instead of training on a fixed dataset, the model processes examples one at a time and simultaneously leverages knowledge from a related source domain to improve predictions on the target domain without requiring large labeled target datasets upfront. | Transfer learning is a machine learning paradigm in which knowledge gained from training a model on a source task or domain is reused to improve learning on a different but related target task or domain. It is especially powerful when labeled data for the target task is scarce, and it underlies most modern deep learning applications in computer vision, natural language processing, and beyond. |
| ScholarGateConjunto de dados ↗ |
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