Tag: federated learning
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AutoFed: Adaptive Federated Traffic Prediction Model
Discover AutoFed, a personalized federated learning model that enhances traffic prediction accuracy while preserving data privacy without manual tuning.
Federated Learning Risks: Dictator Clients Explained
Explore how dictator clients threaten federated learning by disrupting model training and learn strategies to protect decentralized AI systems.
Textual Semantics Boost Federated Learning Prototypes
Discover how textual semantics improve prototype learning in heterogeneous federated learning for better accuracy and faster convergence.
Robust Federated Learning Sync Amid Device Failures
Enhance federated learning with AW-PSP for robust synchronization, fair sampling, and resilience against correlated device failures.
Energy-Efficient Decentralized Federated Learning in IoV
Optimize multi-task federated fine-tuning with energy-aware decentralized scheduling for edge-assisted Internet of Vehicles (IoV) networks.