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Unsupervised Domain Adaptation: Recent Advances and Future Perspectives - Machine Learning: Foundations, Methodologies, and Applications Jingjing Li
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Unsupervised Domain Adaptation: Recent Advances and Future Perspectives - Machine Learning: Foundations, Methodologies, and Applications
Jingjing Li
Unsupervised domain adaptation (UDA) is a challenging problem in machine learning where the model is trained on a source domain with labeled data and tested on a target domain with unlabeled data.
| Medios de comunicación | Libros Paperback Book (Libro con tapa blanda y lomo encolado) |
| Publicado | 23 de abril de 2025 |
| ISBN13 | 9789819710270 |
| Editores | Springer Verlag, Singapore |
| Páginas | 223 |
| Dimensiones | 150 × 220 × 10 mm · 371 g |
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