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cs.LG2023★ 35 cited
Personalized Federated Learning with Feature Alignment and Classifier Collaboration
Jian Xu, Xinyi Tong, Shao-Lun Huang
Data heterogeneity is one of the most challenging issues in federated learning, which motivates a variety of approaches to learn personalized models for participating clients. One…
cs.LG2020★ 10 cited
Input Perturbation: A New Paradigm between Central and Local Differential Privacy
Yilin Kang, Yong Liu, Ben Niu +3
Traditionally, there are two models on differential privacy: the central model and the local model. The central model focuses on the machine learning model and the local model focu…