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Unsupervised Domain Adaptation: Recent Advances and Future Perspectives
English | 2024 | ISBN: 9819710243 | 239 Pages | PDF EPUB (True) | 38 MB
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. In recent years, UDA has received significant attention from the research community due to its applicability in various real-world scenarios. This book provides a comprehensive review of state-of-the-art UDA methods and explores new variants of UDA that have the potential to advance the field.

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