5 papers
Hierarchical Federated Learning for Social Network with Mobility
Zeyu Chen, Wen Chen, Jun Li +5
Federated Learning (FL) offers a decentralized solution that allows collaborative local model training and global aggregation, thereby protecting data privacy. In conventional FL f…
Analysis and Optimization of Wireless Multimodal Federated Learning on Modal Heterogeneity
Xuefeng Han, Wen Chen, Jun Li +6
Multimodal federated learning (MFL) is a distributed framework for training multimodal models without uploading local multimodal data of clients, thereby effectively protecting cli…
Energy-Efficient Wireless Federated Learning via Doubly Adaptive Quantization
Xuefeng Han, Wen Chen, Jun Li +5
Federated learning (FL) has been recognized as a viable distributed learning paradigm for training a machine learning model across distributed clients without uploading raw data. H…
Analysis and Optimization of Wireless Federated Learning with Data Heterogeneity
Xuefeng Han, Jun Li, Wen Chen +4
With the rapid proliferation of smart mobile devices, federated learning (FL) has been widely considered for application in wireless networks for distributed model training. Howeve…
Mobility-Aware Joint User Scheduling and Resource Allocation for Low Latency Federated Learning
Kecheng Fan, Wen Chen, Jun Li +3
As an efficient distributed machine learning approach, Federated learning (FL) can obtain a shared model by iterative local model training at the user side and global model aggrega…