Iterative Methods for Private Synthetic Data: Unifying Framework and New Methods

14 June 2021

Papers citing "Iterative Methods for Private Synthetic Data: Unifying Framework and New Methods"

50 / 51 papers shown

Title
DPolicy: Managing Privacy Risks Across Multiple Releases with Differential Privacy Nicolas Küchler Alexander Viand Hidde Lycklama Anwar Hithnawi 26 0 0 10 May 2025
The DCR Delusion: Measuring the Privacy Risk of Synthetic Data Zexi Yao Natasa Krco Georgi Ganev Yves-Alexandre de Montjoye 145 0 0 02 May 2025
DeSIA: Attribute Inference Attacks Against Limited Fixed Aggregate Statistics Yifeng Mao Bozhidar Stevanoski Yves-Alexandre de Montjoye 49 0 0 25 Apr 2025
Benchmarking Differentially Private Tabular Data Synthesis Kai Chen Xiaochen Li Chen Gong Ryan McKenna Tianhao Wang 28 0 0 18 Apr 2025
Leveraging Vertical Public-Private Split for Improved Synthetic Data Generation Samuel Maddock Shripad Gade Graham Cormode Will Bullock 31 0 0 15 Apr 2025
RAPID: Retrieval Augmented Training of Differentially Private Diffusion Models Tanqiu Jiang Changjiang Li Fenglong Ma Ting Wang 70 0 0 18 Feb 2025
Is API Access to LLMs Useful for Generating Private Synthetic Tabular Data? Marika Swanberg Ryan McKenna Edo Roth Albert Cheu Peter Kairouz 70 0 0 10 Feb 2025
Are Data Experts Buying into Differentially Private Synthetic Data? Gathering Community Perspectives Lucas Rosenblatt Bill Howe Julia Stoyanovich 78 0 0 17 Dec 2024
Privacy without Noisy Gradients: Slicing Mechanism for Generative Model Training Kristjan Greenewald Yuancheng Yu Hao Wang Kai Xu 36 0 0 25 Oct 2024
Efficient and Private Marginal Reconstruction with Local Non-Negativity Brett Mullins Miguel Fuentes Yingtai Xiao Daniel Kifer Cameron Musco Daniel Sheldon 21 1 0 01 Oct 2024
Differentially Private Synthetic High-dimensional Tabular Stream Girish Kumar Thomas Strohmer Roman Vershynin 39 0 0 31 Aug 2024
Grounding and Evaluation for Large Language Models: Practical Challenges and Lessons Learned (Survey) K. Kenthapadi M. Sameki Ankur Taly HILM ELM AILaw 39 12 0 10 Jul 2024
Differentially Private Tabular Data Synthesis using Large Language Models Toan V. Tran Li Xiong SyDa 38 6 0 03 Jun 2024
Private Regression via Data-Dependent Sufficient Statistic Perturbation Cecilia Ferrando Daniel Sheldon 50 0 0 23 May 2024
"What do you want from theory alone?" Experimenting with Tight Auditing of Differentially Private Synthetic Data Generation Meenatchi Sundaram Muthu Selva Annamalai Georgi Ganev Emiliano De Cristofaro 37 9 0 16 May 2024
Privacy-Preserving Instructions for Aligning Large Language Models Da Yu Peter Kairouz Sewoong Oh Zheng Xu 34 17 0 21 Feb 2024
Oracle-Efficient Differentially Private Learning with Public Data Adam Block Mark Bun Rathin Desai Abhishek Shetty Steven Wu FedML 24 2 0 13 Feb 2024
Bounding the Excess Risk for Linear Models Trained on Marginal-Preserving, Differentially-Private, Synthetic Data Yvonne Zhou Mingyu Liang Ivan Brugere Dana Dachman-Soled Danial Dervovic Antigoni Polychroniadou Min Wu 26 1 0 06 Feb 2024
A Bias-Variance Decomposition for Ensembles over Multiple Synthetic Datasets Ossi Raisa Antti Honkela 78 0 0 06 Feb 2024
Privacy-preserving data release leveraging optimal transport and particle gradient descent Konstantin Donhauser Javier Abad Neha Hulkund Fanny Yang 41 4 0 31 Jan 2024
A Simple and Practical Method for Reducing the Disparate Impact of Differential Privacy Lucas Rosenblatt Julia Stoyanovich Christopher Musco 30 2 0 18 Dec 2023
Decentralised, Scalable and Privacy-Preserving Synthetic Data Generation Vishal Ramesh Rui Zhao Naman Goel 32 1 0 30 Oct 2023
Private Synthetic Data Meets Ensemble Learning Haoyuan Sun Navid Azizan Akash Srivastava Hao Wang SyDa 16 1 0 15 Oct 2023
FLAIM: AIM-based Synthetic Data Generation in the Federated Setting Samuel Maddock Graham Cormode Carsten Maple 39 4 0 05 Oct 2023
A Unified View of Differentially Private Deep Generative Modeling Dingfan Chen Raouf Kerkouche Mario Fritz SyDa 26 4 0 27 Sep 2023
DP-TBART: A Transformer-based Autoregressive Model for Differentially Private Tabular Data Generation Rodrigo Castellon Achintya Gopal Brian Bloniarz David S. Rosenberg 21 7 0 19 Jul 2023
CuTS: Customizable Tabular Synthetic Data Generation Mark Vero Mislav Balunović Martin Vechev 26 3 0 07 Jul 2023
Privately generating tabular data using language models Alexandre Sablayrolles Yue Wang Brian Karrer LMTD 21 4 0 07 Jun 2023
Generating Private Synthetic Data with Genetic Algorithms Terrance Liu Jin-Lin Tang G. Vietri Zhiwei Steven Wu SyDa 19 16 0 05 Jun 2023
Harnessing large-language models to generate private synthetic text Alexey Kurakin Natalia Ponomareva Umar Syed Liam MacDermed Andreas Terzis SILM SyDa 31 34 0 02 Jun 2023
Post-processing Private Synthetic Data for Improving Utility on Selected Measures Hao Wang Shivchander Sudalairaj J. Henning Kristjan Greenewald Akash Srivastava 30 6 0 24 May 2023
An Optimal and Scalable Matrix Mechanism for Noisy Marginals under Convex Loss Functions Yingtai Xiao Guanlin He Danfeng Zhang Daniel Kifer 31 4 0 14 May 2023
Synthetic Data in Healthcare Daniel J. McDuff Theodore R. Curran A. Kadambi MedIm SyDa 55 17 0 06 Apr 2023
How to DP-fy ML: A Practical Guide to Machine Learning with Differential Privacy Natalia Ponomareva Hussein Hazimeh Alexey Kurakin Zheng Xu Carson E. Denison H. B. McMahan Sergei Vassilvitskii Steve Chien Abhradeep Thakurta 96 167 0 01 Mar 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
Algorithmically Effective Differentially Private Synthetic Data Yi He Roman Vershynin Yizhe Zhu SyDa 24 8 0 11 Feb 2023
Pushing the Boundaries of Private, Large-Scale Query Answering Brendan Avent Aleksandra Korolova 26 0 0 09 Feb 2023
A Linear Reconstruction Approach for Attribute Inference Attacks against Synthetic Data Meenatchi Sundaram Muthu Selva Annamalai Andrea Gadotti Luc Rocher MIACV 26 21 0 24 Jan 2023
Answering Private Linear Queries Adaptively using the Common Mechanism Yingtai Xiao Guanhong Wang Danfeng Zhang Daniel Kifer 62 7 0 30 Nov 2022
Confidence-Ranked Reconstruction of Census Microdata from Published Statistics Travis Dick Cynthia Dwork Michael Kearns Terrance Liu Aaron Roth G. Vietri Zhiwei Steven Wu 24 29 0 06 Nov 2022
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 36 29 0 15 Sep 2022
MIME: Minority Inclusion for Majority Group Enhancement of AI Performance Pradyumna Chari Yunhao Ba Shreeram S. Athreya A. Kadambi 26 3 0 01 Sep 2022
Epistemic Parity: Reproducibility as an Evaluation Metric for Differential Privacy Lucas Rosenblatt Bernease Herman Anastasia Holovenko Wonkwon Lee Joshua R. Loftus Elizabeth McKinnie Taras Rumezhak Andrii Stadnik Bill Howe Julia Stoyanovich 37 5 0 26 Aug 2022
dpart: Differentially Private Autoregressive Tabular, a General Framework for Synthetic Data Generation Sofiane Mahiou Kai Xu Georgi Ganev SyDa 13 11 0 12 Jul 2022
Private Synthetic Data with Hierarchical Structure Terrance Liu Zhiwei Steven Wu SyDa 19 3 0 13 Jun 2022
Noise-Aware Statistical Inference with Differentially Private Synthetic Data Ossi Raisa Joonas Jälkö Samuel Kaski Antti Honkela SyDa 43 10 0 28 May 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
Relaxed Marginal Consistency for Differentially Private Query Answering Ryan McKenna Siddhant Pradhan Daniel Sheldon G. Miklau 28 11 0 13 Sep 2021
HDMM: Optimizing error of high-dimensional statistical queries under differential privacy Ryan McKenna G. Miklau Michael Hay Ashwin Machanavajjhala 20 20 0 23 Jun 2021
Leveraging Public Data for Practical Private Query Release Terrance Liu G. Vietri Thomas Steinke Jonathan R. Ullman Zhiwei Steven Wu 158 58 0 17 Feb 2021