Interpretable DP
A suite of tools for statistics and machine learning with interpretable risk-based privacy guarantees for easy auditability and communication in regulated environments.
GitHub - interpretable-dp/riskcal: Measure and calibrate operational privacy risks for differentially private algorithms.
github.comMeasure and calibrate operational privacy risks for differentially private algorithms. - interpretable-dp/riskcal
Guest post: Goodbye (ε,δ), hello μ! Reporting privacy guarantees in machine learning - Ted is writing things
Why is Gaussian DP a much better compact representation of privacy guarantees than (ε,δ)-DP, especially for ML applications.