297 citations · 662 across the 9 of their papers we have counts for
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cs.LG2021★ 39 cited
No Fear of Heterogeneity: Classifier Calibration for Federated Learning with Non-IID Data
Mi Luo, Fei Chen, Dapeng Hu +3
A central challenge in training classification models in the real-world federated system is learning with non-IID data. To cope with this, most of the existing works involve enforc…
cs.LG2018★ 270 cited
Federated Meta-Learning with Fast Convergence and Efficient Communication
Fei Chen, Mi Luo, Zhenhua Dong +2
Statistical and systematic challenges in collaboratively training machine learning models across distributed networks of mobile devices have been the bottlenecks in the real-world…