9 citations · 31 across the 26 of their papers we have counts for
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cs.LG2023★ 2 cited
Fake It Till Make It: Federated Learning with Consensus-Oriented Generation
Rui Ye, Yaxin Du, Zhenyang Ni +2
In federated learning (FL), data heterogeneity is one key bottleneck that causes model divergence and limits performance. Addressing this, existing methods often regard data hetero…
cs.LG2023★ 1 cited
Federated Learning Empowered by Generative Content
Rui Ye, Xinyu Zhu, Jingyi Chai +2
Federated learning (FL) enables leveraging distributed private data for model training in a privacy-preserving way. However, data heterogeneity significantly limits the performance…