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
Leveraging Vertical Public-Private Split for Improved Synthetic Data Generation Samuel Maddock Shripad Gade Graham Cormode Will Bullock 26 0 0 15 Apr 2025
Privacy without Noisy Gradients: Slicing Mechanism for Generative Model Training Kristjan Greenewald Yuancheng Yu Hao Wang Kai Xu 29 0 0 25 Oct 2024
Privacy-Preserving Instructions for Aligning Large Language Models Da Yu Peter Kairouz Sewoong Oh Zheng Xu 32 17 0 21 Feb 2024
Private Synthetic Data Meets Ensemble Learning Haoyuan Sun Navid Azizan Akash Srivastava Hao Wang SyDa 11 1 0 15 Oct 2023
Continual Release of Differentially Private Synthetic Data from Longitudinal Data Collections Mark Bun Marco Gaboardi Marcel Neunhoeffer Wanrong Zhang SyDa 11 7 0 13 Jun 2023
Machine Learning for Synthetic Data Generation: A Review Ying-Cheng Lu Minjie Shen Huazheng Wang Xiao Wang Capucine Van Rechem Tianfan Fu Wenqi Wei SyDa 18 136 0 08 Feb 2023
Robin Hood and Matthew Effects: Differential Privacy Has Disparate Impact on Synthetic Data Georgi Ganev Bristena Oprisanu Emiliano De Cristofaro 26 57 0 23 Sep 2021
Leveraging Public Data for Practical Private Query Release Terrance Liu G. Vietri Thomas Steinke Jonathan R. Ullman Zhiwei Steven Wu 142 58 0 17 Feb 2021
Private Post-GAN Boosting Marcel Neunhoeffer Zhiwei Steven Wu Cynthia Dwork 100 29 0 23 Jul 2020