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Unified Robust and Convergent Over-The-Air Federated Learning under Channel Noise and Heterogeneity
Federated learning (FL) has emerged as a key enabler of distributed model training across ubiquitous wireless edge devices while preserving data privacy in next-generation wireless systems. One communication-efficient approach to realize this is leveraging Over-the-Air Federated Learning (OTA-FL), w
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