13 citations · 14 across the 2 of their papers we have counts for
2 papers
cs.LG2022★ 13 cited
Achieving Personalized Federated Learning with Sparse Local Models
Tiansheng Huang, Shiwei Liu, Li Shen +3
Federated learning (FL) is vulnerable to heterogeneously distributed data, since a common global model in FL may not adapt to the heterogeneous data distribution of each user. To c…
cs.LG2021★ 1 cited
Variation-Incentive Loss Re-weighting for Regression Analysis on Biased Data
Wentai Wu, Ligang He, Weiwei Lin
Both classification and regression tasks are susceptible to the biased distribution of training data. However, existing approaches are focused on the class-imbalanced learning and…