On synthetic cardiac data, FedCVR — a re-implementation of FedAdam with server-side momentum — is reported to reach F1 0.78 / AUC 0.96 under DP (ε≈13.4), beating stateless and other adaptive baselines, though the paper's own numbers conflict internally.
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A Robust Framework for Secure Cardiovascular Risk Prediction: An Architectural Case Study of Differentially Private Federated Learning
On synthetic cardiac data, FedCVR — a re-implementation of FedAdam with server-side momentum — is reported to reach F1 0.78 / AUC 0.96 under DP (ε≈13.4), beating stateless and other adaptive baselines, though the paper's own numbers conflict internally.