Fedaca: An adaptive communication-efficient asynchronous framework for federated learning

S Zhou, Y Huo, S Bao, B Landman… - … Computing and Self …, 2022 - ieeexplore.ieee.org
Federated Learning (FL) is a type of distributed machine learning, which avoids sharing
privacy and sensitive data with a central server. Despite the advances in FL, current …
被引用次数：4 相关文章
[PDF] vanderbilt.edu

[PDF][PDF] FedACA: An Adaptive Communication-Efficient Asynchronous Framework for Federated Learning

S Zhou, Y Huo, S Bao, B Landman, A Gokhale - dre.vanderbilt.edu
Federated Learning (FL) is a type of distributed machine learning, which avoids sharing
privacy and sensitive data with a central server. Despite the advances in FL, current …

FedACA: An Adaptive Communication-Efficient Asynchronous Framework for Federated Learning

S Zhou, Y Huo, S Bao, B Landman… - 2022 IEEE International …, 2022 - computer.org
Federated Learning (FL) is a type of distributed machine learning, which avoids sharing
privacy and sensitive data with a central server. Despite the advances in FL, current …