Renyi Differential Privacy
PulseAugur coverage of Renyi Differential Privacy — every cluster mentioning Renyi Differential Privacy across labs, papers, and developer communities, ranked by signal.
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New Federated GNN Framework Enhances Privacy and Communication Efficiency
Researchers have developed CE-FedGNN, a novel framework for federated graph neural networks designed to enhance communication efficiency and privacy. This method avoids sharing raw data or frequent embedding exchanges b…
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New framework offers optimal guarantees for auditing RDP machine learning
Researchers have developed a new auditing framework for machine learning algorithms that claim Rényi differential privacy (RDP). This framework uses the Donsker-Varadhan (DV) estimator to directly measure Rényi divergen…
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New privacy mechanism links geometric analysis, heat diffusion, and DP
Researchers have introduced a new privacy mechanism designed for data residing on Riemannian manifolds. This novel approach establishes connections between geometric analysis, heat diffusion models, and differential pri…