arXiv stat.ML
· Papers
CPDA: Class-Conditional Path Distribution Alignment for Unsupervised Time-Series Domain Adaptation
arXiv:2608.09193v1 Announce Type: new Abstract: Unsupervised time-series domain adaptation (DA) addresses the challenge of transferring a classifier from a labeled source domain to an unlabeled target domain under distribution shifts induced by different users, sensors, devices, acquisition conditions, or temporal dyna