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FedRAD: Federated Robust Adaptive Distillation
The robustness of federated learning (FL) is vital for the distributed training of an accurate global model that is shared among large number of clients.
Robust Aggregation for Adaptive Privacy Preserving Federated Learning in Healthcare
In this work, we implement and evaluate different robust aggregation methods in FL applied to healthcare data.
Cryptography and Security
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