Fedlga: Toward system-heterogeneity of federated learning via local gradient approximation

X Li, Z Qu, B Tang, Z Lu - IEEE Transactions on Cybernetics, 2023 - ieeexplore.ieee.org
Federated learning (FL) is a decentralized machine learning architecture, which leverages a
large number of remote devices to learn a joint model with distributed training data …
被引用次数：21 相关文章

FedLGA: Toward System-Heterogeneity of Federated Learning via Local Gradient Approximation

X Li, Z Qu, B Tang, Z Lu - IEEE transactions on …, 2024 - pubmed.ncbi.nlm.nih.gov
Federated learning (FL) is a decentralized machine learning architecture, which leverages a
large number of remote devices to learn a joint model with distributed training data …

FedLGA: Toward System-Heterogeneity of Federated Learning via Local Gradient Approximation.

X Li, Z Qu, B Tang, Z Lu - IEEE Transactions on Cybernetics, 2023 - europepmc.org
Federated learning (FL) is a decentralized machine learning architecture, which leverages a
large number of remote devices to learn a joint model with distributed training data …

[引用][C] FedLGA: Toward System-Heterogeneity of Federated Learning via Local Gradient Approximation

X Li, Z Qu, B Tang, Z Lu - IEEE Transactions on Cybernetics, 2023 - par.nsf.gov

FedLGA: Towards System-Heterogeneity of Federated Learning via Local Gradient Approximation

X Li, Z Qu, B Tang, Z Lu - arXiv preprint arXiv:2112.11989, 2021 - arxiv.org
Federated Learning (FL) is a decentralized machine learning architecture, which leverages
a large number of remote devices to learn a joint model with distributed training data …

FedLGA: Towards System-Heterogeneity of Federated Learning via Local Gradient Approximation

X Li, Z Qu, B Tang, Z Lu - arXiv e-prints, 2021 - ui.adsabs.harvard.edu
Federated Learning (FL) is a decentralized machine learning architecture, which leverages
a large number of remote devices to learn a joint model with distributed training data …