most citedAdaptive Gradient Sparsification for Efficient Federated Learning: An Online Learning Approach

9 citations · 12 across the 4 of their papers we have counts for

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cs.LG2023

Optimization Design for Federated Learning in Heterogeneous 6G Networks

Bing Luo, Xiaomin Ouyang, Peng Sun +3

With the rapid advancement of 5G networks, billions of smart Internet of Things (IoT) devices along with an enormous amount of data are generated at the network edge. While still a…

cs.LG2020★ 3 cited

Robustness and Diversity Seeking Data-Free Knowledge Distillation

Pengchao Han, Jihong Park, Shiqiang Wang +1

Knowledge distillation (KD) has enabled remarkable progress in model compression and knowledge transfer. However, KD requires a large volume of original data or their representatio…

cs.LG2020★ 9 cited

Adaptive Gradient Sparsification for Efficient Federated Learning: An Online Learning Approach

Pengchao Han, Shiqiang Wang, Kin K. Leung

Federated learning (FL) is an emerging technique for training machine learning models using geographically dispersed data collected by local entities. It includes local computation…