Author

Lei Yang

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Sep 2026

Bias Mitigation in Federated Learning Through Feature Integration

Machine learning models are trained on datasets where undesired features have spurious correlations with the target variable, resulting in the bias shifts of the model output to a different class. In federated learning (FL), a common problem is data distribution skew. Since each client has a different distribution, mod...

Zi-Yi Zhang, Ming-Xuan Ouyang, Kun-Hao Li et al. · ACM Transactions on Knowledg... · 0 citations

Open access Jul 2026

Personalized Data-Free Knowledge Distillation for Federated Learning under Heterogeneous Models and Data

PDKD solves the problem of model drift caused by the inconsistent distribution of distillation datasets and the local data by generating personalized distillation datasets for each client while protecting client data privacy.

Jing-feng Tu, Lei Yang, Chao Ma et al. · ACM Transactions on Knowledg... · 0 citations