The Composition Theorem for Differential Privacy

4 November 2013

Pramod Viswanath

Papers citing "The Composition Theorem for Differential Privacy"

50 / 139 papers shown

Title
Ensure Differential Privacy and Convergence Accuracy in Consensus Tracking and Aggregative Games with Coupling Constraints Yongqiang Wang 25 3 0 28 Oct 2022
Privately Fine-Tuning Large Language Models with Differential Privacy R. Behnia Mohammadreza Ebrahimi Jason L. Pacheco B. Padmanabhan 24 44 0 26 Oct 2022
Generalised Likelihood Ratio Testing Adversaries through the Differential Privacy Lens Georgios Kaissis Alexander Ziller Stefan Kolek Martinez de Azagra Daniel Rueckert 12 0 0 24 Oct 2022
DPIS: An Enhanced Mechanism for Differentially Private SGD with Importance Sampling Jianxin Wei Ergute Bao X. Xiao Yifan Yang 46 20 0 18 Oct 2022
A General Framework for Auditing Differentially Private Machine Learning Fred Lu Joseph Munoz Maya Fuchs Tyler LeBlond Elliott Zaresky-Williams Edward Raff Francis Ferraro Brian Testa FedML 22 35 0 16 Oct 2022
CANIFE: Crafting Canaries for Empirical Privacy Measurement in Federated Learning Samuel Maddock Alexandre Sablayrolles Pierre Stock FedML 17 22 0 06 Oct 2022
Federated Boosted Decision Trees with Differential Privacy Samuel Maddock Graham Cormode Tianhao Wang Carsten Maple S. Jha FedML 26 29 0 06 Oct 2022
On the Statistical Complexity of Estimation and Testing under Privacy Constraints Clément Lalanne Aurélien Garivier Rémi Gribonval 27 7 0 05 Oct 2022
Composition of Differential Privacy & Privacy Amplification by Subsampling Thomas Steinke 61 49 0 02 Oct 2022
On the Impossible Safety of Large AI Models El-Mahdi El-Mhamdi Sadegh Farhadkhani R. Guerraoui Nirupam Gupta L. Hoang Rafael Pinot Sébastien Rouault John Stephan 30 31 0 30 Sep 2022
On the Choice of Databases in Differential Privacy Composition Valentin Hartmann Vincent Bindschaedler Robert West 26 0 0 27 Sep 2022
Bayesian and Frequentist Semantics for Common Variations of Differential Privacy: Applications to the 2020 Census Daniel Kifer John M. Abowd Robert Ashmead Ryan Cumings-Menon Philip Leclerc Ashwin Machanavajjhala William Sexton Pavel I Zhuravlev 48 26 0 07 Sep 2022
Age-Dependent Differential Privacy Meng Zhang Ermin Wei R. Berry Jianwei Huang 15 37 0 03 Sep 2022
Differential Privacy on Dynamic Data Yuan Qiu K. Yi 26 0 0 03 Sep 2022
The Saddle-Point Accountant for Differential Privacy Wael Alghamdi S. Asoodeh Flavio du Pin Calmon Juan Felipe Gomez O. Kosut Lalitha Sankar Fei Wei 17 7 0 20 Aug 2022
FedDM: Iterative Distribution Matching for Communication-Efficient Federated Learning Yuanhao Xiong Ruochen Wang Minhao Cheng Felix X. Yu Cho-Jui Hsieh FedML DD 47 82 0 20 Jul 2022
Faster Privacy Accounting via Evolving Discretization Badih Ghazi Pritish Kamath Ravi Kumar Pasin Manurangsi 57 14 0 10 Jul 2022
Connect the Dots: Tighter Discrete Approximations of Privacy Loss Distributions Vadym Doroshenko Badih Ghazi Pritish Kamath Ravi Kumar Pasin Manurangsi 16 40 0 10 Jul 2022
Measuring Forgetting of Memorized Training Examples Matthew Jagielski Om Thakkar Florian Tramèr Daphne Ippolito Katherine Lee ... Eric Wallace Shuang Song Abhradeep Thakurta Nicolas Papernot Chiyuan Zhang TDI 54 102 0 30 Jun 2022
Cactus Mechanisms: Optimal Differential Privacy Mechanisms in the Large-Composition Regime Wael Alghamdi S. Asoodeh Flavio du Pin Calmon O. Kosut Lalitha Sankar Fei Wei 11 8 0 25 Jun 2022
Brownian Noise Reduction: Maximizing Privacy Subject to Accuracy Constraints Justin Whitehouse Zhiwei Steven Wu Aaditya Ramdas Ryan M. Rogers 11 9 0 15 Jun 2022
Bayesian Estimation of Differential Privacy Santiago Zanella Béguelin Lukas Wutschitz Shruti Tople A. Salem Victor Rühle Andrew J. Paverd Mohammad Naseri Boris Köpf Daniel Jones 17 36 0 10 Jun 2022
Analytical Composition of Differential Privacy via the Edgeworth Accountant Hua Wang Sheng-yang Gao Huanyu Zhang Milan Shen Weijie J. Su FedML 28 21 0 09 Jun 2022
On the Privacy Properties of GAN-generated Samples Zinan Lin Vyas Sekar Giulia Fanti PICV 21 26 0 03 Jun 2022
Privacy for Free: How does Dataset Condensation Help Privacy? Tian Dong Bo-Lu Zhao Lingjuan Lyu DD 24 113 0 01 Jun 2022
Noise-Aware Statistical Inference with Differentially Private Synthetic Data Ossi Raisa Joonas Jälkö Samuel Kaski Antti Honkela SyDa 40 10 0 28 May 2022
$Privacy accounting $\varepsilon$conomics: Improving differential privacy composition via a posteriori bounds$ Privacy accounting $\varepsilon$ conomics: Improving differential privacy composition via a posteriori bounds Valentin Hartmann Vincent Bindschaedler Alexander Bentkamp Robert West 21 1 0 06 May 2022
Differentially Private Triangle and 4-Cycle Counting in the Shuffle Model Jacob Imola Takao Murakami Kamalika Chaudhuri 19 23 0 03 May 2022
Adaptive Private-K-Selection with Adaptive K and Application to Multi-label PATE Yuqing Zhu Yu-Xiang Wang 35 18 0 30 Mar 2022
Differential Privacy Amplification in Quantum and Quantum-inspired Algorithms Armando Angrisani Mina Doosti E. Kashefi 21 12 0 07 Mar 2022
Continual and Sliding Window Release for Private Empirical Risk Minimization Lauren Watson Abhirup Ghosh Benedek Rozemberczki Rik Sarkar 16 0 0 07 Mar 2022
Does Label Differential Privacy Prevent Label Inference Attacks? Ruihan Wu Jinfu Zhou Kilian Q. Weinberger Chuan Guo 23 15 0 25 Feb 2022
Bounding Membership Inference Anvith Thudi Ilia Shumailov Franziska Boenisch Nicolas Papernot 33 18 0 24 Feb 2022
Debugging Differential Privacy: A Case Study for Privacy Auditing Florian Tramèr Andreas Terzis Thomas Steinke Shuang Song Matthew Jagielski Nicholas Carlini 17 42 0 24 Feb 2022
Differentially Private Speaker Anonymization Ali Shahin Shamsabadi B. M. L. Srivastava A. Bellet Nathalie Vauquier Emmanuel Vincent Mohamed Maouche Marc Tommasi Nicolas Papernot MIACV 46 32 0 23 Feb 2022
Better Private Algorithms for Correlation Clustering Daogao Liu 28 8 0 22 Feb 2022
Quantum Differential Privacy: An Information Theory Perspective C. Hirche Cambyse Rouzé Daniel Stilck França 33 60 0 22 Feb 2022
Private Quantiles Estimation in the Presence of Atoms Clément Lalanne C. Gastaud Nicolas Grislain Aurélien Garivier Rémi Gribonval 20 7 0 15 Feb 2022
Plume: Differential Privacy at Scale Kareem Amin Jennifer Gillenwater Matthew Joseph Alex Kulesza Sergei Vassilvitskii 34 9 0 27 Jan 2022
Reconstructing Training Data with Informed Adversaries Borja Balle Giovanni Cherubin Jamie Hayes MIACV AAML 43 158 0 13 Jan 2022
Gradient Leakage Attack Resilient Deep Learning Wenqi Wei Ling Liu SILM PILM AAML 27 46 0 25 Dec 2021
Randomized Response Mechanisms for Differential Privacy Data Analysis: Bounds and Applications Fei Ma Ping Wang 28 4 0 14 Dec 2021
OPTT: Optimal Piecewise Transformation Technique for Analyzing Numerical Data under Local Differential Privacy Fei Ma Renbo Zhu Ping Wang 14 1 0 09 Dec 2021
Membership Inference Attacks From First Principles Nicholas Carlini Steve Chien Milad Nasr Shuang Song Andreas Terzis Florian Tramèr MIACV MIALM 29 639 0 07 Dec 2021
Network Traffic Shaping for Enhancing Privacy in IoT Systems Sijie Xiong Anand D. Sarwate N. Mandayam 10 16 0 29 Nov 2021
Differentially Private Federated Learning on Heterogeneous Data Maxence Noble A. Bellet Aymeric Dieuleveut FedML 13 102 0 17 Nov 2021
Distribution-Invariant Differential Privacy Xuan Bi Xiaotong Shen 16 13 0 08 Nov 2021
DP-XGBoost: Private Machine Learning at Scale Cheng Cheng Wei Dai 16 8 0 25 Oct 2021
Adaptive Differentially Private Empirical Risk Minimization Xiaoxia Wu Lingxiao Wang Irina Cristali Quanquan Gu Rebecca Willett 38 6 0 14 Oct 2021
Generalization Techniques Empirically Outperform Differential Privacy against Membership Inference Jiaxiang Liu Simon Oya Florian Kerschbaum MIACV 14 9 0 11 Oct 2021