19 citations · 36 across the 19 of their papers we have counts for
4 papers · 1 filter
Hierarchical Federated Learning in Wireless Networks: Pruning Tackles Bandwidth Scarcity and System Heterogeneity
Md Ferdous Pervej, Richeng Jin, Huaiyu Dai
While a practical wireless network has many tiers where end users do not directly communicate with the central server, the users' devices have limited computation and battery power…
Distributed Learning over Networks with Graph-Attention-Based Personalization
Zhuojun Tian, Zhaoyang Zhang, Zhaohui Yang +2
In conventional distributed learning over a network, multiple agents collaboratively build a common machine learning model. However, due to the underlying non-i.i.d. data distribut…
Magnitude Matters: Fixing SIGNSGD Through Magnitude-Aware Sparsification in the Presence of Data Heterogeneity
Richeng Jin, Xiaofan He, Caijun Zhong +3
Communication overhead has become one of the major bottlenecks in the distributed training of deep neural networks. To alleviate the concern, various gradient compression methods h…
Breaking the Communication-Privacy-Accuracy Tradeoff with -Differential Privacy
Richeng Jin, Zhonggen Su, Caijun Zhong +3
We consider a federated data analytics problem in which a server coordinates the collaborative data analysis of multiple users with privacy concerns and limited communication capab…