Hierarchical federated learning in wireless networks: Pruning tackles bandwidth scarcity and system heterogeneity
While a practical wireless network has many tiers where end users do not directly
communicate with the central server, the users' devices have limited computation and …
communicate with the central server, the users' devices have limited computation and …
Distillation-Based User Selection for Heterogeneous Federated Learning
B Li, W Li - International Journal of Network Dynamics and …, 2024 - sciltp.com
Federated learning is a newly developing distributed machine learning technology, which
makes it possible for users to train machine learning models with decentralized privacy data …
makes it possible for users to train machine learning models with decentralized privacy data …
Adaptive Clustering based Straggler-aware Federated Learning in Wireless Edge Networks
Federated learning (FL) has been vigorously promoted in wireless edge networks as it
fosters collaborative training of machine learning (ML) models while preserving individual …
fosters collaborative training of machine learning (ML) models while preserving individual …
Device Scheduling and Bandwidth Allocation for Federated Learning over Wireless Networks
Federated Learning (FL) has been widely used to train shared machine learning models
while addressing the privacy concerns. When deployed in wireless networks, bandwidth …
while addressing the privacy concerns. When deployed in wireless networks, bandwidth …