Unsupervised Domain Adaptation

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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...

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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...

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  • Formats: pdf
  • ISBN: 9789819710256
  • Publication Date: 22 Apr 2024
  • Publisher: Springer Nature Singapore
  • Product language: English
  • Drm Setting: DRM