Resources#
Background#
Learning About Differential Privacy#
Courses & Educational Materials from the Harvard University Privacy Tools Project
Designing Access with Differential Privacy
Papers#
The Complexity of Differential Privacy
Calibrating Noise to Sensitivity in Private Data Analysis (Laplace mechanism)
On Significance of the Least Significant Bits For Differential Privacy (Snapping mechanism and how floating-point numbers and the laplace mechanism leak)
Mechanism Design via Differential Privacy (Exponential mechanism)
Differential Privacy on Finite Computers (Geometric mechanism)
Privacy-preserving Statistical Estimation with Optimal Convergence Rates (Sample/aggregate and quantiles)
Deep Learning with Differential Privacy (Gradient descent)
U.S. Broadband Coverage Data Set: A Differentially Private Data Release