Fedaux: An efficient framework for hybrid federated learning
As an enabler of sixth-generation communication technology (6G), Federated Learning (FL)
triggers a paradigm shift from" connected things" to" connected intelligence". FL implements …
triggers a paradigm shift from" connected things" to" connected intelligence". FL implements …
Performance optimization of federated learning over mobile wireless networks
In this paper, the problem of training federated learning (FL) algorithms over a wireless
network with mobile users is studied. In the considered model, several mobile users and a …
network with mobile users is studied. In the considered model, several mobile users and a …
Joint resource management and model compression for wireless federated learning
We consider the problem of convergence time minimization for federated learning (FL)
implemented in wireless systems. In such setups, each wireless edge device transmits its …
implemented in wireless systems. In such setups, each wireless edge device transmits its …
Client selection and bandwidth allocation for federated learning: An online optimization perspective
Federated learning (FL) can train a global model from clients' local data set, which can make
full use of the computing resources of clients and performs more extensive and efficient …
full use of the computing resources of clients and performs more extensive and efficient …
Optimizing federated learning on device heterogeneity with a sampling strategy
X Xu, S Duan, J Zhang, Y Luo… - 2021 IEEE/ACM 29th …, 2021 - ieeexplore.ieee.org
Federated learning (FL) is a novel machine learning that performs distributed training locally
on devices and aggregating the local models into a global one. The limited network …
on devices and aggregating the local models into a global one. The limited network …
Resource management and fairness for federated learning over wireless edge networks
R Balakrishnan, M Akdeniz, S Dhakal… - 2020 IEEE 21st …, 2020 - ieeexplore.ieee.org
Federated Learning has the potential to break the barrier of AI adoption at the edge through
better data privacy and reduced client to server communication cost. However, the …
better data privacy and reduced client to server communication cost. However, the …
[引用][C] Multi-server over-the-air federated learning
SM Azimi-Abarghouyi, V Fodor - arXiv preprint arXiv:2211.16162, 2022
FedBroadcast: Exploit broadcast channel for fast convergence in wireless federated learning
With the fast development of modern networking technologies, the transmission rate and
reliability of wireless networks have been greatly improved. Meanwhile, the fast-developing …
reliability of wireless networks have been greatly improved. Meanwhile, the fast-developing …
Adaptive hierarchical federated learning over wireless networks
Federated learning (FL) is promising in enabling large-scale model training by massive
devices without exposing their local datasets. However, due to limited wireless resources …
devices without exposing their local datasets. However, due to limited wireless resources …
On the convergence time of federated learning over wireless networks under imperfect CSI
Federated learning (FL) has recently emerged as an attractive decentralized solution for
wireless networks to collaboratively train a shared model while keeping data localized. As a …
wireless networks to collaboratively train a shared model while keeping data localized. As a …