Adaptive configuration for heterogeneous participants in decentralized federated learning

Y Liao, Y Xu, H Xu, L Wang… - IEEE INFOCOM 2023-IEEE …, 2023 - ieeexplore.ieee.org
Data generated at the network edge can be processed locally by leveraging the paradigm of
edge computing (EC). Aided by EC, decentralized federated learning (DFL), which …
被引用次数：27 相关文章
[PDF] researchgate.net

[PDF][PDF] Adaptive Configuration for Heterogeneous Participants in Decentralized Federated Learning

Y Liao, Y Xu, H Xu, L Wang, C Qian - arXiv preprint arXiv …, 2022 - researchgate.net
Data generated at the network edge can be processed locally by leveraging the paradigm of
edge computing (EC). Aided by EC, decentralized federated learning (DFL), which …
[PDF] ucsc.edu

[PDF][PDF] Adaptive Configuration for Heterogeneous Participants in Decentralized Federated Learning

Y Liao, Y Xu, H Xu, L Wang, C Qian - users.soe.ucsc.edu
Data generated at the network edge can be processed locally by leveraging the paradigm of
edge computing (EC). Aided by EC, decentralized federated learning (DFL), which …

Adaptive Configuration for Heterogeneous Participants in Decentralized Federated Learning

Y Liao, Y Xu, H Xu, L Wang, C Qian - arXiv preprint arXiv:2212.02136, 2022 - arxiv.org
Data generated at the network edge can be processed locally by leveraging the paradigm of
edge computing (EC). Aided by EC, decentralized federated learning (DFL), which …

Adaptive Configuration for Heterogeneous Participants in Decentralized Federated Learning

Y Liao, Y Xu, H Xu, L Wang, C Qian - arXiv e-prints, 2022 - ui.adsabs.harvard.edu
Data generated at the network edge can be processed locally by leveraging the paradigm of
edge computing (EC). Aided by EC, decentralized federated learning (DFL), which …