49 citations · 103 across the 21 of their papers we have counts for
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cs.LG2021
How global observation works in Federated Learning: Integrating vertical training into Horizontal Federated Learning
Shuo Wan, Jiaxun Lu, Pingyi Fan +3
Federated learning (FL) has recently emerged as a transformative paradigm that jointly train a model with distributed data sets in IoT while avoiding the need for central data coll…
cs.LG2021★ 8 cited
Unified Group Fairness on Federated Learning
Fengda Zhang, Kun Kuang, Yuxuan Liu +6
Federated learning (FL) has emerged as an important machine learning paradigm where a global model is trained based on the private data from distributed clients. However, most of e…
cs.LG2021★ 3 cited
Convergence Analysis and System Design for Federated Learning over Wireless Networks
Shuo Wan, Jiaxun Lu, Pingyi Fan +3
Federated learning (FL) has recently emerged as an important and promising learning scheme in IoT, enabling devices to jointly learn a model without sharing their raw data sets. Ho…