Post-processing Private Synthetic Data for Improving Utility on Selected
Measures

Post-processing Private Synthetic Data for Improving Utility on Selected Measures

24 May 2023

Shivchander Sudalairaj

Kristjan Greenewald

Akash Srivastava

Papers citing "Post-processing Private Synthetic Data for Improving Utility on Selected Measures"

9 / 9 papers shown

Title
Private Synthetic Data for Multitask Learning and Marginal Queries G. Vietri Cédric Archambeau Sergul Aydore William Brown Michael Kearns Aaron Roth Ankit Siva Shuai Tang Zhiwei Steven Wu SyDa 53 29 0 15 Sep 2022
Bias Mitigation for Machine Learning Classifiers: A Comprehensive Survey Max Hort Zhenpeng Chen Jie M. Zhang Mark Harman Federica Sarro FaML AI4CE 46 167 0 14 Jul 2022
Benchmarking Differentially Private Synthetic Data Generation Algorithms Yuchao Tao Ryan McKenna Michael Hay Ashwin Machanavajjhala G. Miklau SyDa 47 83 0 16 Dec 2021
Winning the NIST Contest: A scalable and general approach to differentially private synthetic data Ryan McKenna G. Miklau Daniel Sheldon SyDa 26 119 0 11 Aug 2021
Iterative Methods for Private Synthetic Data: Unifying Framework and New Methods Terrance Liu G. Vietri Zhiwei Steven Wu SyDa 43 61 0 14 Jun 2021
Differentially Private Query Release Through Adaptive Projection Sergul Aydore William Brown Michael Kearns K. Kenthapadi Luca Melis Aaron Roth Ankit Siva 62 64 0 11 Mar 2021
New Oracle-Efficient Algorithms for Private Synthetic Data Release G. Vietri Grace Tian Mark Bun Thomas Steinke Zhiwei Steven Wu SyDa 138 76 0 10 Jul 2020
Graphical-model based estimation and inference for differential privacy Ryan McKenna Daniel Sheldon G. Miklau 44 140 0 26 Jan 2019
Improving the Gaussian Mechanism for Differential Privacy: Analytical Calibration and Optimal Denoising Borja Balle Yu Wang MLT 47 395 0 16 May 2018

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