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Ruidong Fan

2 accepted papers

2025

Label Shift Meets Online Learning: Ensuring Consistent Adaptation with Universal Dynamic Regret

CVPR 2025highlight

Label shift, which investigates the adaptation of label distributions between the fixed source and target domains, has attracted significant research interests and broad applications in offline settings. In real-world scenarios, however, data often arrives as a continuous stream. Addressing label sh…

Cited by 0SourcePDFScholar
2025

One-step Label Shift Adaptation via Robust Weight Estimation

IJCAI 2025

Label shift is a prevalent phenomenon encountered in open environments, characterized by a notable discrepancy in the label distributions between the source (training) and target (test) domains, whereas the conditional distributions given the labels remain invariant. Existing label shift methods ado

Cited by 0SourcePDFScholar