OTA-FFL uses an epsilon-constrained Chebyshev objective to set adaptive client weights and closed-form transmit scalars for over-the-air federated learning.
Communication-efficient learning of networks from decentralized data,
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Over-the-Air Fair Federated Learning via Multi-Objective Optimization
OTA-FFL uses an epsilon-constrained Chebyshev objective to set adaptive client weights and closed-form transmit scalars for over-the-air federated learning.