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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.
| Media | Bøker Pocketbok (Bok med mykt omslag og limt rygg) |
| Utgitt | 23. april 2025 |
| ISBN13 | 9789819710270 |
| Utgivere | Springer Verlag, Singapore |
| Antall sider | 223 |
| Mål | 150 × 220 × 10 mm · 371 g |
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