1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.LG2023
Federated Learning on Virtual Heterogeneous Data with Local-global Distillation
Chun-Yin Huang, Ruinan Jin, Can Zhao +2
While Federated Learning (FL) is gaining popularity for training machine learning models in a decentralized fashion, numerous challenges persist, such as asynchronization, computat…
cs.LG2021★ 1 cited
Accelerating Federated Learning with a Global Biased Optimiser
Jed Mills, Jia Hu, Geyong Min +3
Federated Learning (FL) is a recent development in distributed machine learning that collaboratively trains models without training data leaving client devices, preserving data pri…