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cs.LG2026
Cluster-Aware Over-the-Air Federated Learning with Energy-Harvesting Devices: From Global Training to Model Personalization
Furkan Bagci, Busra Tegin, Mohammad Kazemi +1
Federated learning (FL) enables distributed optimization and learning across decentralized edge devices while preserving data privacy, but its performance is fundamentally constrai…
cs.LG2025
Update Estimation and Scheduling for Over-the-Air Federated Learning with Energy Harvesting Devices
Furkan Bagci, Busra Tegin, Mohammad Kazemi +1
We study over-the-air (OTA) federated learning (FL) for energy harvesting devices with heterogeneous data distribution over wireless fading multiple access channel (MAC). To addres…
cs.LG2025
Over-the-Air Multi-Sensor Inference with Neural Networks Using Memristor-Based Analog Computing
Busra Tegin, Muhammad Atif Ali, Tolga M Duman
Deep neural networks provide reliable solutions for many classification and regression tasks; however, their application in real-time wireless systems with simple sensor networks i…