Differentially Private Post-Processing for Fair Regression

7 May 2024

Papers citing "Differentially Private Post-Processing for Fair Regression"

6 / 6 papers shown

Title
Learning with Differentially Private (Sliced) Wasserstein Gradients David Rodríguez-Vítores Clément Lalanne Jean-Michel Loubes FedML 46 0 0 03 Feb 2025
The Pitfalls of "Security by Obscurity" And What They Mean for Transparent AI Peter Hall Olivia Mundahl Sunoo Park 78 0 0 30 Jan 2025
The Role of Adaptive Optimizers for Honest Private Hyperparameter Selection Shubhankar Mohapatra Sajin Sasy Xi He Gautam Kamath Om Thakkar 114 32 0 09 Nov 2021
Hyperparameter Tuning with Renyi Differential Privacy Nicolas Papernot Thomas Steinke 135 120 0 07 Oct 2021
On the Sample Complexity of Privately Learning Unbounded High-Dimensional Gaussians Ishaq Aden-Ali H. Ashtiani Gautam Kamath 42 42 0 19 Oct 2020
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments Alexandra Chouldechova FaML 207 2,091 0 24 Oct 2016