A federated learning pipeline that combines confidence-based label cleaning, collaborative conditional GAN training, and FedProx improves macro-F1 over noisy FedAvg and FedProx baselines on MNIST and Fashion-MNIST, with cleaning alone responsible for most of the improvement.
A survey of federated learning for edge computing: Research problems and solutions,
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Robust Federated Learning with Confidence-Weighted Filtering and GAN-Based Completion under Noisy and Incomplete Data
A federated learning pipeline that combines confidence-based label cleaning, collaborative conditional GAN training, and FedProx improves macro-F1 over noisy FedAvg and FedProx baselines on MNIST and Fashion-MNIST, with cleaning alone responsible for most of the improvement.