4 citations · 6 across the 3 of their papers we have counts for
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cs.LG2022★ 1 cited
Graph Federated Learning with Hidden Representation Sharing
Shuang Wu, Mingxuan Zhang, Yuantong Li +2
Learning on Graphs (LoG) is widely used in multi-client systems when each client has insufficient local data, and multiple clients have to share their raw data to learn a model of…
cs.LG2022★ 4 cited
Self-Aware Personalized Federated Learning
Huili Chen, Jie Ding, Eric Tramel +4
In the context of personalized federated learning (FL), the critical challenge is to balance local model improvement and global model tuning when the personal and global objectives…
cs.LG2022★ 1 cited
Federated Learning Challenges and Opportunities: An Outlook
Jie Ding, Eric Tramel, Anit Kumar Sahu +3
Federated learning (FL) has been developed as a promising framework to leverage the resources of edge devices, enhance customers' privacy, comply with regulations, and reduce devel…