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Clustered Vehicular Federated Learning: Process and Optimization
Post-processing Counterexample-guided Fairness Guarantees in Neural Networks
Data-Aware Device Scheduling for Federated Edge Learning
Data-Quality Based Scheduling for Federated Edge Learning
Empowering Prosumer Communities in Smart Grid with Wireless Communications and Federated Edge Learning
Scaling Guarantees for Nearest Counterfactual Explanations
Electrical Load Forecasting Using Edge Computing and Federated Learning
Faster Algorithms for Quantitative Analysis of MCs and MDPs with Small Treewidth
Federated Edge Learning: Design Issues and Challenges