Recovering clinical utility under differential privacy: empirical validation of adaptive federated aggregation on heterogeneous cardiovascular datasets
Read the original at arxiv.org→arXiv:2607.19403v1 Announce Type: new Abstract: Validating federated learning frameworks on real clinical data is an essential step between proof-of-concept demonstrations in controlled synthetic environments and...
Original headline: "Recovering Clinical Utility Under Differential Privacy: Empirical Validation of Adaptive Federated Aggregation on Heterogeneous Cardiovascular Datasets"
Coverage timeline
- Jul 23, 04:00 UTC arXiv cs.LG lead source Recovering Clinical Utility Under Differential Privacy: Empirical Validation of Adaptive Federated Aggregation on Heterogeneous Cardiovascular Datasets