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New Oracle-Efficient Algorithms for Private Synthetic Data Release

New Oracle-Efficient Algorithms for Private Synthetic Data Release

10 July 2020
G. Vietri
Grace Tian
Mark Bun
Thomas Steinke
Zhiwei Steven Wu
    SyDa
ArXiv (abs)PDFHTML

Papers citing "New Oracle-Efficient Algorithms for Private Synthetic Data Release"

50 / 52 papers shown
Title
dpmm: Differentially Private Marginal Models, a Library for Synthetic Tabular Data Generation
dpmm: Differentially Private Marginal Models, a Library for Synthetic Tabular Data Generation
Sofiane Mahiou
Amir Dizche
Reza Nazari
Xinmin Wu
Ralph Abbey
Jorge Silva
Georgi Ganev
32
0
0
31 May 2025
Benchmarking Differentially Private Tabular Data Synthesis
Benchmarking Differentially Private Tabular Data Synthesis
Kai Chen
Xiaochen Li
Chen Gong
Ryan McKenna
Tianhao Wang
76
2
0
18 Apr 2025
Understanding the Impact of Data Domain Extraction on Synthetic Data Privacy
Georgi Ganev
Meenatchi Sundaram Muthu Selva Annamalai
Sofiane Mahiou
Emiliano De Cristofaro
MIACV
107
1
0
11 Apr 2025
The Importance of Being Discrete: Measuring the Impact of Discretization in End-to-End Differentially Private Synthetic Data
The Importance of Being Discrete: Measuring the Impact of Discretization in End-to-End Differentially Private Synthetic Data
Georgi Ganev
Meenatchi Sundaram Muthu Selva Annamalai
Sofiane Mahiou
Emiliano De Cristofaro
69
3
0
09 Apr 2025
PSGraph: Differentially Private Streaming Graph Synthesis by Considering Temporal Dynamics
PSGraph: Differentially Private Streaming Graph Synthesis by Considering Temporal Dynamics
Quan Yuan
Zhikun Zhang
L. Du
Min Chen
Mingyang Sun
Yunjun Gao
Michael Backes
Shibo He
Jiming Chen
181
0
0
16 Dec 2024
Privacy without Noisy Gradients: Slicing Mechanism for Generative Model
  Training
Privacy without Noisy Gradients: Slicing Mechanism for Generative Model Training
Kristjan Greenewald
Yuancheng Yu
Hao Wang
Kai Xu
135
2
0
25 Oct 2024
Private Regression via Data-Dependent Sufficient Statistic Perturbation
Private Regression via Data-Dependent Sufficient Statistic Perturbation
Cecilia Ferrando
Daniel Sheldon
95
1
0
23 May 2024
Privacy-Enhanced Database Synthesis for Benchmark Publishing (Technical Report)
Privacy-Enhanced Database Synthesis for Benchmark Publishing (Technical Report)
Yongrui Zhong
Yunqing Ge
Jianbin Qin
Yongrui Zhong
Bo Tang
Yu-Xuan Qiu
Rui Mao
Ye Yuan
Makoto Onizuka
Chuan Xiao
107
1
0
02 May 2024
Exploration is Harder than Prediction: Cryptographically Separating
  Reinforcement Learning from Supervised Learning
Exploration is Harder than Prediction: Cryptographically Separating Reinforcement Learning from Supervised Learning
Noah Golowich
Ankur Moitra
Dhruv Rohatgi
OffRL
75
4
0
04 Apr 2024
Joint Selection: Adaptively Incorporating Public Information for Private
  Synthetic Data
Joint Selection: Adaptively Incorporating Public Information for Private Synthetic Data
Miguel Fuentes
Brett Mullins
Ryan McKenna
G. Miklau
Daniel Sheldon
73
5
0
12 Mar 2024
Privacy-Preserving Instructions for Aligning Large Language Models
Privacy-Preserving Instructions for Aligning Large Language Models
Da Yu
Peter Kairouz
Sewoong Oh
Zheng Xu
115
25
0
21 Feb 2024
Oracle-Efficient Differentially Private Learning with Public Data
Oracle-Efficient Differentially Private Learning with Public Data
Adam Block
Mark Bun
Rathin Desai
Abhishek Shetty
Steven Wu
FedML
53
2
0
13 Feb 2024
Benchmarking Private Population Data Release Mechanisms: Synthetic Data
  vs. TopDown
Benchmarking Private Population Data Release Mechanisms: Synthetic Data vs. TopDown
Aadyaa Maddi
Swadhin Routray
Alexander Goldberg
Giulia Fanti
51
0
0
31 Jan 2024
Privacy-preserving data release leveraging optimal transport and
  particle gradient descent
Privacy-preserving data release leveraging optimal transport and particle gradient descent
Konstantin Donhauser
Javier Abad
Neha Hulkund
Fanny Yang
94
5
0
31 Jan 2024
A Study on Training and Developing Large Language Models for Behavior
  Tree Generation
A Study on Training and Developing Large Language Models for Behavior Tree Generation
Fu Li
Xueying Wang
Bin Li
Yunlong Wu
Yanzhen Wang
Xiaodong Yi
67
5
0
16 Jan 2024
A Simple and Practical Method for Reducing the Disparate Impact of
  Differential Privacy
A Simple and Practical Method for Reducing the Disparate Impact of Differential Privacy
Lucas Rosenblatt
Julia Stoyanovich
Christopher Musco
59
2
0
18 Dec 2023
Private Synthetic Data Meets Ensemble Learning
Private Synthetic Data Meets Ensemble Learning
Haoyuan Sun
Navid Azizan
Akash Srivastava
Hao Wang
SyDa
39
1
0
15 Oct 2023
Partition-based differentially private synthetic data generation
Partition-based differentially private synthetic data generation
Meifan Zhang
Dihang Deng
Lihua Yin
47
0
0
10 Oct 2023
A Unified View of Differentially Private Deep Generative Modeling
A Unified View of Differentially Private Deep Generative Modeling
Dingfan Chen
Raouf Kerkouche
Mario Fritz
SyDa
80
5
0
27 Sep 2023
DP-PQD: Privately Detecting Per-Query Gaps In Synthetic Data Generated
  By Black-Box Mechanisms
DP-PQD: Privately Detecting Per-Query Gaps In Synthetic Data Generated By Black-Box Mechanisms
Shweta Patwa
Danyu Sun
Amir Gilad
Ashwin Machanavajjhala
Sudeepa Roy
43
1
0
15 Sep 2023
SoK: Privacy-Preserving Data Synthesis
SoK: Privacy-Preserving Data Synthesis
Yuzheng Hu
Fan Wu
Yue Liu
Yunhui Long
Gonzalo Munilla Garrido
Chang Ge
Bolin Ding
David A. Forsyth
Yue Liu
Basel Alomair
116
33
0
05 Jul 2023
Turbo: Effective Caching in Differentially-Private Databases
Turbo: Effective Caching in Differentially-Private Databases
Kelly Kostopoulou
Pierre Tholoniat
Asaf Cidon
Roxana Geambasu
Mathias Lécuyer
70
2
0
28 Jun 2023
Continual Release of Differentially Private Synthetic Data from
  Longitudinal Data Collections
Continual Release of Differentially Private Synthetic Data from Longitudinal Data Collections
Mark Bun
Marco Gaboardi
Marcel Neunhoeffer
Wanrong Zhang
SyDa
58
8
0
13 Jun 2023
Generating Private Synthetic Data with Genetic Algorithms
Generating Private Synthetic Data with Genetic Algorithms
Terrance Liu
Jin-Lin Tang
G. Vietri
Zhiwei Steven Wu
SyDa
70
18
0
05 Jun 2023
Post-processing Private Synthetic Data for Improving Utility on Selected
  Measures
Post-processing Private Synthetic Data for Improving Utility on Selected Measures
Hao Wang
Shivchander Sudalairaj
J. Henning
Kristjan Greenewald
Akash Srivastava
60
6
0
24 May 2023
An Optimal and Scalable Matrix Mechanism for Noisy Marginals under
  Convex Loss Functions
An Optimal and Scalable Matrix Mechanism for Noisy Marginals under Convex Loss Functions
Yingtai Xiao
Guanlin He
Qiang Yan
Daniel Kifer
107
4
0
14 May 2023
PrivGraph: Differentially Private Graph Data Publication by Exploiting
  Community Information
PrivGraph: Differentially Private Graph Data Publication by Exploiting Community Information
Quan Yuan
Zhikun Zhang
L. Du
Min Chen
Peng Cheng
Mingyang Sun
82
19
0
05 Apr 2023
Coincidental Generation
Coincidental Generation
Jordan W. Suchow
Necdet Gurkan
52
0
0
03 Apr 2023
Differentially Private Algorithms for Synthetic Power System Datasets
Differentially Private Algorithms for Synthetic Power System Datasets
V. Dvorkin
A. Botterud
30
10
0
20 Mar 2023
How to DP-fy ML: A Practical Guide to Machine Learning with Differential
  Privacy
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
156
183
0
01 Mar 2023
Pushing the Boundaries of Private, Large-Scale Query Answering
Pushing the Boundaries of Private, Large-Scale Query Answering
Brendan Avent
Aleksandra Korolova
78
0
0
09 Feb 2023
Private Set Generation with Discriminative Information
Private Set Generation with Discriminative Information
Dingfan Chen
Raouf Kerkouche
Mario Fritz
DD
80
39
0
07 Nov 2022
PrivTrace: Differentially Private Trajectory Synthesis by Adaptive
  Markov Model
PrivTrace: Differentially Private Trajectory Synthesis by Adaptive Markov Model
Haiming Wang
Zhikun Zhang
Tianhao Wang
Shibo He
Michael Backes
Jiming Chen
Yang Zhang
129
40
0
02 Oct 2022
Private Synthetic Data for Multitask Learning and Marginal Queries
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
92
31
0
15 Sep 2022
Epistemic Parity: Reproducibility as an Evaluation Metric for
  Differential Privacy
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
56
5
0
26 Aug 2022
dpart: Differentially Private Autoregressive Tabular, a General
  Framework for Synthetic Data Generation
dpart: Differentially Private Autoregressive Tabular, a General Framework for Synthetic Data Generation
Sofiane Mahiou
Kai Xu
Georgi Ganev
SyDa
54
12
0
12 Jul 2022
Private Synthetic Data with Hierarchical Structure
Private Synthetic Data with Hierarchical Structure
Terrance Liu
Zhiwei Steven Wu
SyDa
44
3
0
13 Jun 2022
Noise-Aware Statistical Inference with Differentially Private Synthetic
  Data
Noise-Aware Statistical Inference with Differentially Private Synthetic Data
Ossi Raisa
Hibiki Ito
Samuel Kaski
Antti Honkela
SyDa
90
11
0
28 May 2022
Statistical Data Privacy: A Song of Privacy and Utility
Statistical Data Privacy: A Song of Privacy and Utility
Aleksandra B. Slavkovic
Jeremy Seeman
42
27
0
06 May 2022
Benchmarking Differentially Private Synthetic Data Generation Algorithms
Benchmarking Differentially Private Synthetic Data Generation Algorithms
Yuchao Tao
Ryan McKenna
Michael Hay
Ashwin Machanavajjhala
G. Miklau
SyDa
102
87
0
16 Dec 2021
Relaxed Marginal Consistency for Differentially Private Query Answering
Relaxed Marginal Consistency for Differentially Private Query Answering
Ryan McKenna
Siddhant Pradhan
Daniel Sheldon
G. Miklau
88
11
0
13 Sep 2021
Winning the NIST Contest: A scalable and general approach to
  differentially private synthetic data
Winning the NIST Contest: A scalable and general approach to differentially private synthetic data
Ryan McKenna
G. Miklau
Daniel Sheldon
SyDa
73
127
0
11 Aug 2021
DPSyn: Experiences in the NIST Differential Privacy Data Synthesis
  Challenges
DPSyn: Experiences in the NIST Differential Privacy Data Synthesis Challenges
Ninghui Li
Zhikun Zhang
Tianhao Wang
147
18
0
24 Jun 2021
HDMM: Optimizing error of high-dimensional statistical queries under
  differential privacy
HDMM: Optimizing error of high-dimensional statistical queries under differential privacy
Ryan McKenna
G. Miklau
Michael Hay
Ashwin Machanavajjhala
63
20
0
23 Jun 2021
Interval Privacy: A Framework for Privacy-Preserving Data Collection
Interval Privacy: A Framework for Privacy-Preserving Data Collection
Jie Ding
Bangjun Ding
75
6
0
17 Jun 2021
Iterative Methods for Private Synthetic Data: Unifying Framework and New
  Methods
Iterative Methods for Private Synthetic Data: Unifying Framework and New Methods
Terrance Liu
G. Vietri
Zhiwei Steven Wu
SyDa
70
64
0
14 Jun 2021
Rejoinder: Gaussian Differential Privacy
Rejoinder: Gaussian Differential Privacy
Jinshuo Dong
Aaron Roth
Weijie J. Su
38
2
0
05 Apr 2021
Differentially Private Query Release Through Adaptive Projection
Differentially Private Query Release Through Adaptive Projection
Sergul Aydore
William Brown
Michael Kearns
K. Kenthapadi
Luca Melis
Aaron Roth
Ankit Siva
95
68
0
11 Mar 2021
Leveraging Public Data for Practical Private Query Release
Leveraging Public Data for Practical Private Query Release
Terrance Liu
G. Vietri
Thomas Steinke
Jonathan R. Ullman
Zhiwei Steven Wu
198
60
0
17 Feb 2021
PrivSyn: Differentially Private Data Synthesis
PrivSyn: Differentially Private Data Synthesis
Zhikun Zhang
Tianhao Wang
Ninghui Li
Jean Honorio
Michael Backes
Shibo He
Jiming Chen
Yang Zhang
SyDa
68
64
0
30 Dec 2020
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