2 citations · 2 across the 4 of their papers we have counts for
4 papers · 1 filter
Fedcompass: Federated Clustered and Periodic Aggregation Framework for Hybrid Classical-Quantum Models
Yueheng Wang, Xing He, Zinuo Cai +4
Federated learning enables collaborative model training across decentralized clients under privacy constraints. Quantum computing offers potential for alleviating computational and…
A Two-Timescale Approach for Wireless Federated Learning with Parameter Freezing and Power Control
Jinhao Ouyang, Yuan Liu, Hang Liu
Federated learning (FL) enables distributed devices to train a shared machine learning (ML) model collaboratively while protecting their data privacy. However, the resource-limited…
Asynchronous Wireless Federated Learning with Probabilistic Client Selection
Jiarong Yang, Yuan Liu, Fangjiong Chen +2
Federated learning (FL) is a promising distributed learning framework where distributed clients collaboratively train a machine learning model coordinated by a server. To tackle th…
Accelerating Split Federated Learning over Wireless Communication Networks
Ce Xu, Jinxuan Li, Yuan Liu +2
The development of artificial intelligence (AI) provides opportunities for the promotion of deep neural network (DNN)-based applications. However, the large amount of parameters an…