Feature-Space Planes Searcher: A Universal Domain Adaptation Framework for Interpretability and Computational Efficiency

Summary

The paper proposes Feature-space Planes Searcher (FPS), an unsupervised domain adaptation framework that corrects decision-boundary misalignment while keeping a pre-trained feature encoder frozen. It argues this avoids the cost and unpredictable distortions of fine-tuning, and adds an Intra-Class Distance Metric (ICDM) for label-free hyperparameter selection. The authors report competitive benchmark results and applications including protein structure prediction, remote sensing classification and earthquake detection.