25 citations · 27 across the 2 of their papers we have counts for
3 papers
cs.LG2022★ 2 cited
GlueFL: Reconciling Client Sampling and Model Masking for Bandwidth Efficient Federated Learning
Shiqi He, Qifan Yan, Feijie Wu +3
Federated learning (FL) is an effective technique to directly involve edge devices in machine learning training while preserving client privacy. However, the substantial communicat…
cs.LG2021★ 25 cited
Parameterized Knowledge Transfer for Personalized Federated Learning
Jie Zhang, Song Guo, Xiaosong Ma +3
In recent years, personalized federated learning (pFL) has attracted increasing attention for its potential in dealing with statistical heterogeneity among clients. However, the st…
math.OC2020
On the Convergence of Quantized Parallel Restarted SGD for Central Server Free Distributed Training
Feijie Wu, Shiqi He, Yutong Yang +4
Communication is a crucial phase in the context of distributed training. Because parameter server (PS) frequently experiences network congestion, recent studies have found that tra…