2 papers
cs.LG2022
Exploiting Personalized Invariance for Better Out-of-distribution Generalization in Federated Learning
Xueyang Tang, Song Guo, Jie Zhang
Recently, data heterogeneity among the training datasets on the local clients (a.k.a., Non-IID data) has attracted intense interest in Federated Learning (FL), and many personalize…
cs.LG2021
Personalized Federated Learning with Contextualized Generalization
Xueyang Tang, Song Guo, Jingcai Guo
The prevalent personalized federated learning (PFL) usually pursues a trade-off between personalization and generalization by maintaining a shared global model to guide the trainin…