2 papers
cs.DC2024
Measuring Data Similarity for Efficient Federated Learning: A Feasibility Study
Fernanda Famá, Charalampos Kalalas, Sandra Lagen +1
In multiple federated learning schemes, a random subset of clients sends in each round their model updates to the server for aggregation. Although this client selection strategy ai…
cs.LG2023
Towards Energy-Aware Federated Traffic Prediction for Cellular Networks
Vasileios Perifanis, Nikolaos Pavlidis, Selim F. Yilmaz +6
Cellular traffic prediction is a crucial activity for optimizing networks in fifth-generation (5G) networks and beyond, as accurate forecasting is essential for intelligent network…