FedGSCA aggregates client-level GMM noise selectors and uses adaptive pseudo-labels with a credal-set robust loss to improve federated medical image classification under label noise.
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FedGSCA: Medical Federated Learning with Global Sample Selector and Client Adaptive Adjuster under Label Noise
FedGSCA aggregates client-level GMM noise selectors and uses adaptive pseudo-labels with a credal-set robust loss to improve federated medical image classification under label noise.