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We provide the optimal receive combining strategy for federated learning inmultiple-input multiple-output (MIMO) systems. Our proposed algorithm allowsthe clients to perform individual gradient sparsification which greatlyimproves performance in scenarios with heterogeneous (non i.i.d.) trainingdata. The proposed method beats the benchmark by a wide margin.

Optimal MIMO Combining for Blind Federated Edge Learning with Gradient Sparsification