Author

Nicolò Michelusi

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Preprint Oct 2026

Budget-Constrained Multi-Consensus Decentralized Gradient Descent

We investigate decentralized gradient descent (DGD) with emphasis on efficient communication and computation resource utilization under budget constraints. As a first step toward the broader communication-computation allocation problem, we consider and analyze a \textit{multi-consensus decentralized gradient descent} (...

Shu-Yi Ren, Nicolò Michelusi, Erik G. Larsson · 0 citations

#machine learning Book Open access 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. · Proceedings of the Twenty-se... · 0 citations

#machine learning Preprint Sep 2026

Non-Coherent Over-the-Air Federated Learning: Protocol, Convergence, and Device Scheduling

To mitigate the scalability bottleneck in the radio access network (RAN) in federated edge learning (FEEL), over-the-air federated learning (AirFL) exploits waveform superposition over multiple-access channels (MACs) for analog model aggregation. However, coherent AirFL typically relies on stringent PHY-layer condition...

Hai-Feng Wen, Nicolò Michelusi, Osvaldo Simeone et al. · 0 citations