most citedCommunication Efficient Federated Learning with Adaptive Quantization

1 citations · 1 across the 2 of their papers we have counts for

collaborators

2 papers

cs.LG2021

DQ-SGD: Dynamic Quantization in SGD for Communication-Efficient Distributed Learning

Guangfeng Yan, Shao-Lun Huang, Tian Lan +1

Gradient quantization is an emerging technique in reducing communication costs in distributed learning. Existing gradient quantization algorithms often rely on engineering heuristi…

cs.DC2021★ 1 cited

Communication Efficient Federated Learning with Adaptive Quantization

Yuzhu Mao, Zihao Zhao, Guangfeng Yan +4

Federated learning (FL) has attracted tremendous attentions in recent years due to its privacy preserving measures and great potentials in some distributed but privacy-sensitive ap…