At typical differential privacy levels, Cox models lose significance for about 90% of covariates and drop to random predictive performance, with usable results requiring much weaker privacy.
The algorithmic foundations of differential privacy,
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Benchmarking the Utility of Privacy-Preserving Cox Regression Under Data-Driven Clipping Bounds: A Multi-Dataset Simulation Study
At typical differential privacy levels, Cox models lose significance for about 90% of covariates and drop to random predictive performance, with usable results requiring much weaker privacy.
- Privacy-Preserving Proof of Human Authorship via Zero-Knowledge Process Attestation