Author

Li-Li Su

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#machine learning Preprint Sep 2026

Over-the-Air Federated Learning in Heterogeneous Mobile Wireless Networks

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 simultaneous model aggregation. Most existing work struggles with heterogeneous fading channels. These approaches either enforce unbiased up...

Ming Xiang, Nicolò Michelusi, Y. Eldar et al. · 0 citations

#machine learning Preprint Sep 2026

Resilience Beyond Stationary Client Unavailability: Unlocking Efficient and Unbiased Federated Learning

FedSWE is proposed, which admits novel algorithmic structures to compensate for missed computations, stabilize and diffuse the global updates over rounds, and evenly mix the local updates through implicit gossiping, despite being agnostic to non-stationary dynamics.

Ming Xiang, Stratis Ioannidis, Edmund Yeh et al. · 0 citations