Fair Decision Making using Privacy-Protected Data

1 code implementation • 29 May 2019 • Satya Kuppam, Ryan McKenna, David Pujol, Michael Hay, Ashwin Machanavajjhala, Gerome Miklau

Data collected about individuals is regularly used to make decisions that impact those same individuals.

Databases

Differentially Private Learning of Graphical Models using CGMs

no code implementations • ICML 2017 • Garrett Bernstein, Ryan McKenna, Tao Sun, Daniel Sheldon, Michael Hay, Gerome Miklau

A naive learning algorithm that uses the noisy sufficient statistics “as is” outperforms general-purpose differentially private learning algorithms.

Differentially Private Learning of Undirected Graphical Models using Collective Graphical Models

no code implementations • 14 Jun 2017 • Garrett Bernstein, Ryan McKenna, Tao Sun, Daniel Sheldon, Michael Hay, Gerome Miklau

We investigate the problem of learning discrete, undirected graphical models in a differentially private way.

Principled Evaluation of Differentially Private Algorithms using DPBench

1 code implementation • 15 Dec 2015 • Michael Hay, Ashwin Machanavajjhala, Gerome Miklau, Yan Chen, Dan Zhang

Differential privacy has become the dominant standard in the research community for strong privacy protection.

Databases Cryptography and Security