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cs.LG2026
Over-the-Air Federated Learning in Heterogeneous Mobile Wireless Networks
Ming Xiang, Nicolò Michelusi, Yonina C. Eldar +1
Over-the-air computation has emerged as a scalable and efficient solution for deploying federated learning algorithms in wireless networks by exploiting waveform superposition for…
cs.LG2026
Resilience Beyond Stationary Client Unavailability: Unlocking Efficient and Unbiased Federated Learning
Ming Xiang, Stratis Ioannidis, Edmund Yeh +2
Due to resource constraints or external and internal uncertainties, clients in real-world federated learning systems are often intermittently available edge devices. In highly dyna…