Leveraging Public Data for Practical Private Query Release

Leveraging Public Data for Practical Private Query Release

17 February 2021

Jonathan R. Ullman

Zhiwei Steven Wu

Papers citing "Leveraging Public Data for Practical Private Query Release"

19 / 19 papers shown

Title
RAPID: Retrieval Augmented Training of Differentially Private Diffusion Models Tanqiu Jiang Changjiang Li Fenglong Ma Ting Wang 70 0 0 18 Feb 2025
Credit Attribution and Stable Compression Roi Livni Shay Moran Kobbi Nissim Chirag Pabbaraju 49 0 0 22 Jun 2024
Private Distribution Learning with Public Data: The View from Sample Compression Shai Ben-David Alex Bie C. Canonne Gautam Kamath Vikrant Singhal 42 11 0 11 Aug 2023
Differentially Private Heavy Hitter Detection using Federated Analytics Karan N. Chadha Junye Chen John C. Duchi Vitaly Feldman H. Hashemi O. Javidbakht Audra McMillan Kunal Talwar FedML 21 7 0 21 Jul 2023
Selective Pre-training for Private Fine-tuning Da Yu Sivakanth Gopi Janardhan Kulkarni Zinan Lin Saurabh Naik Tomasz Religa Jian Yin Huishuai Zhang 35 19 0 23 May 2023
An Optimal and Scalable Matrix Mechanism for Noisy Marginals under Convex Loss Functions Yingtai Xiao Guanlin He Danfeng Zhang Daniel Kifer 29 4 0 14 May 2023
30 Years of Synthetic Data Joerg Drechsler Anna Haensch 30 15 0 04 Apr 2023
Certified private data release for sparse Lipschitz functions Konstantin Donhauser J. Lokna Amartya Sanyal M. Boedihardjo R. Honig Fanny Yang 46 3 0 19 Feb 2023
Answering Private Linear Queries Adaptively using the Common Mechanism Yingtai Xiao Guanhong Wang Danfeng Zhang Daniel Kifer 60 7 0 30 Nov 2022
Private Estimation with Public Data Alex Bie Gautam Kamath Vikrant Singhal 36 28 0 16 Aug 2022
When Does Differentially Private Learning Not Suffer in High Dimensions? Xuechen Li Daogao Liu Tatsunori Hashimoto Huseyin A. Inan Janardhan Kulkarni Y. Lee Abhradeep Thakurta 32 58 0 01 Jul 2022
Benchmarking Differentially Private Synthetic Data Generation Algorithms Yuchao Tao Ryan McKenna Michael Hay Ashwin Machanavajjhala G. Miklau SyDa 33 82 0 16 Dec 2021
Public Data-Assisted Mirror Descent for Private Model Training Ehsan Amid Arun Ganesh Rajiv Mathews Swaroop Indra Ramaswamy Shuang Song Thomas Steinke Vinith M. Suriyakumar Om Thakkar Abhradeep Thakurta 13 49 0 01 Dec 2021
Differentially Private Fine-tuning of Language Models Da Yu Saurabh Naik A. Backurs Sivakanth Gopi Huseyin A. Inan ... Y. Lee Andre Manoel Lukas Wutschitz Sergey Yekhanin Huishuai Zhang 134 346 0 13 Oct 2021
Private sampling: a noiseless approach for generating differentially private synthetic data M. Boedihardjo Thomas Strohmer Roman Vershynin SyDa 29 14 0 30 Sep 2021
Iterative Methods for Private Synthetic Data: Unifying Framework and New Methods Terrance Liu G. Vietri Zhiwei Steven Wu SyDa 22 61 0 14 Jun 2021
Deep Learning with Label Differential Privacy Badih Ghazi Noah Golowich Ravi Kumar Pasin Manurangsi Chiyuan Zhang 42 144 0 11 Feb 2021
Permute-and-Flip: A new mechanism for differentially private selection Ryan McKenna Daniel Sheldon 112 47 0 23 Oct 2020
Private Post-GAN Boosting Marcel Neunhoeffer Zhiwei Steven Wu Cynthia Dwork 116 29 0 23 Jul 2020