The article presents a novel graph Spectral Alignment (SPA) framework for unsupervised domain adaptation (UDA) in machine learning. The SPA framework aims to extend the in-domain model to distinctive target…
Continue readingThis research tackles challenges in unsupervised domain adaptation (UDA), where the goal is to perform well in a distribution shifted domain without labels. The authors develop an importance weighted group…
Continue readingThe article presents a novel approach to Unsupervised Domain Adaptation (UDA) called Invariant Consistency Learning (ICON). Traditional UDA methods often suffer from spurious correlations between domain-invariant and domain-specific features, which…
Continue readingThis study investigates the potential of unsupervised domain adaptation (UDA) methods in improving the accuracy and fairness of skin lesion classification. The researchers leverage multiple skin lesion datasets to assess…
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