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Combining Model-Agnostic Meta-Learning and Transfer Learning for Regression
For cases in which a machine learning model needs to be adapted to a new task, various approaches have been developed, including model-agnostic meta-learning (MAML) and transfer learning. In this paper, we investigate how the differences in the data distributions between the old tasks and the new ta...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9865593/ https://www.ncbi.nlm.nih.gov/pubmed/36679376 http://dx.doi.org/10.3390/s23020583 |