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cs.CV2024★ 1 cited
Contrastive Conditional Alignment based on Label Shift Calibration for Imbalanced Domain Adaptation
Xiaona Sun, Zhenyu Wu, Zhiqiang Zhan +1
Many existing unsupervised domain adaptation (UDA) methods primarily focus on covariate shift, limiting their effectiveness in imbalanced domain adaptation (IDA) where both covaria…
cs.LG2024
Decoupled Federated Learning on Long-Tailed and Non-IID data with Feature Statistics
Zhuoxin Chen, Zhenyu Wu, Yang Ji
Federated learning is designed to enhance data security and privacy, but faces challenges when dealing with heterogeneous data in long-tailed and non-IID distributions. This paper…