Concentrated Differential Privacy: Simplifications, Extensions, and Lower Bounds

6 May 2016

Papers citing "Concentrated Differential Privacy: Simplifications, Extensions, and Lower Bounds"

50 / 207 papers shown

Title
CoinPress: Practical Private Mean and Covariance Estimation Sourav Biswas Yihe Dong Gautam Kamath Jonathan R. Ullman 39 115 0 11 Jun 2020
Revisiting Membership Inference Under Realistic Assumptions Bargav Jayaraman Lingxiao Wang Katherine Knipmeyer Quanquan Gu David Evans 24 147 0 21 May 2020
Privacy Preserving Face Recognition Utilizing Differential Privacy Pathum Chamikara Mahawaga Arachchige P. Bertók I. Khalil D. Liu S. Çamtepe PICV 50 117 0 21 May 2020
Private Stochastic Convex Optimization: Optimal Rates in Linear Time Vitaly Feldman Tomer Koren Kunal Talwar 10 203 0 10 May 2020
A Primer on Private Statistics Gautam Kamath Jonathan R. Ullman 38 48 0 30 Apr 2020
Input Perturbation: A New Paradigm between Central and Local Differential Privacy Yilin Kang Yong Liu Ben Niu Xin-Yi Tong Likun Zhang Weiping Wang 27 11 0 20 Feb 2020
LinkedIn's Audience Engagements API: A Privacy Preserving Data Analytics System at Scale Ryan M. Rogers S. Subramaniam Sean Peng D. Durfee Seunghyun Lee Santosh Kumar Kancha Shraddha Sahay P. Ahammad 27 77 0 14 Feb 2020
Guidelines for Implementing and Auditing Differentially Private Systems Daniel Kifer Solomon Messing Aaron Roth Abhradeep Thakurta Danfeng Zhang 16 34 0 10 Feb 2020
Efficient, Noise-Tolerant, and Private Learning via Boosting Mark Bun M. Carmosino Jessica Sorrell FedML 16 17 0 04 Feb 2020
Reasoning About Generalization via Conditional Mutual Information Thomas Steinke Lydia Zakynthinou 23 160 0 24 Jan 2020
Encode, Shuffle, Analyze Privacy Revisited: Formalizations and Empirical Evaluation Ulfar Erlingsson Vitaly Feldman Ilya Mironov A. Raghunathan Shuang Song Kunal Talwar Abhradeep Thakurta 29 83 0 10 Jan 2020
Differentially Private Confidence Intervals Wenxin Du C. Foot Monica Moniot Andrew Bray Adam Groce 20 45 0 07 Jan 2020
Reviewing and Improving the Gaussian Mechanism for Differential Privacy Jun Zhao Teng Wang Tao Bai Kwok-Yan Lam Zhiying Xu Shuyu Shi Xuebin Ren Xinyu Yang Yang Liu Han Yu 44 30 0 27 Nov 2019
Federated Learning with Bayesian Differential Privacy Aleksei Triastcyn Boi Faltings FedML 19 174 0 22 Nov 2019
Providing Input-Discriminative Protection for Local Differential Privacy Xiaolan Gu Ming Li Li Xiong Yang Cao 19 41 0 04 Nov 2019
Composition Properties of Bayesian Differential Privacy Jun Zhao 12 1 0 02 Nov 2019
A New Analysis of Differential Privacy's Generalization Guarantees Christopher Jung Katrina Ligett Seth Neel Aaron Roth Saeed Sharifi-Malvajerdi Moshe Shenfeld FedML 21 47 0 09 Sep 2019
Differentially Private SQL with Bounded User Contribution Royce J. Wilson Celia Yuxin Zhang William K. C. Lam Damien Desfontaines Daniel Simmons-Marengo Bryant Gipson 27 147 0 04 Sep 2019
Rényi Differential Privacy of the Sampled Gaussian Mechanism Ilya Mironov Kunal Talwar Li Zhang 28 278 0 28 Aug 2019
Privacy-Preserving Tensor Factorization for Collaborative Health Data Analysis Jing Ma Qiuchen Zhang Jian Lou Joyce C. Ho Li Xiong Xiaoqian Jiang 30 44 0 26 Aug 2019
Local Differential Privacy for Deep Learning Pathum Chamikara Mahawaga Arachchige P. Bertók I. Khalil Dongxi Liu S. Çamtepe Mohammed Atiquzzaman 41 220 0 08 Aug 2019
DP-LSSGD: A Stochastic Optimization Method to Lift the Utility in Privacy-Preserving ERM Bao Wang Quanquan Gu M. Boedihardjo Farzin Barekat Stanley J. Osher 16 25 0 28 Jun 2019
Average-Case Averages: Private Algorithms for Smooth Sensitivity and Mean Estimation Mark Bun Thomas Steinke 47 74 0 06 Jun 2019
Locally Differentially Private Data Collection and Analysis Teng Wang Jun Zhao Xinyu Yang Xuebin Ren 27 13 0 05 Jun 2019
SoK: Differential Privacies Damien Desfontaines Balázs Pejó 33 122 0 04 Jun 2019
Private Identity Testing for High-Dimensional Distributions C. Canonne Gautam Kamath Audra McMillan Jonathan R. Ullman Lydia Zakynthinou 37 36 0 28 May 2019
KNG: The K-Norm Gradient Mechanism M. Reimherr Jordan Awan 29 23 0 23 May 2019
Practical Differentially Private Top- $k$ Selection with Pay-what-you-get Composition D. Durfee Ryan M. Rogers 23 82 0 10 May 2019
Evaluating Differentially Private Machine Learning in Practice Bargav Jayaraman David Evans 15 7 0 24 Feb 2019
Lower Bounds for Locally Private Estimation via Communication Complexity John C. Duchi Ryan M. Rogers 13 93 0 01 Feb 2019
Differentially Private Markov Chain Monte Carlo Mikko A. Heikkilä Joonas Jälkö O. Dikmen Antti Honkela 27 25 0 29 Jan 2019
Differentially Private ADMM for Distributed Medical Machine Learning Jiahao Ding Xiaoqi Qin Wenjun Xu Yanmin Gong Zhu Han Miao Pan FedML 32 20 0 07 Jan 2019
A Hybrid Approach to Privacy-Preserving Federated Learning Stacey Truex Nathalie Baracaldo Ali Anwar Thomas Steinke Heiko Ludwig Rui Zhang Yi Zhou FedML 19 884 0 07 Dec 2018
Protection Against Reconstruction and Its Applications in Private Federated Learning Abhishek Bhowmick John C. Duchi Julien Freudiger Gaurav Kapoor Ryan M. Rogers FedML 24 357 0 03 Dec 2018
Amplification by Shuffling: From Local to Central Differential Privacy via Anonymity Ulfar Erlingsson Vitaly Feldman Ilya Mironov A. Raghunathan Kunal Talwar Abhradeep Thakurta 150 420 0 29 Nov 2018
Differentially Private Contextual Linear Bandits R. Shariff Or Sheffet 6 114 0 28 Sep 2018
Chorus: a Programming Framework for Building Scalable Differential Privacy Mechanisms Noah M. Johnson Joseph P. Near J. M. Hellerstein D. Song 22 24 0 20 Sep 2018
Concentrated Differentially Private Gradient Descent with Adaptive per-Iteration Privacy Budget Jaewoo Lee Daniel Kifer 22 156 0 28 Aug 2018
Privacy Amplification by Iteration Vitaly Feldman Ilya Mironov Kunal Talwar Abhradeep Thakurta FedML 20 170 0 20 Aug 2018
Subsampled Rényi Differential Privacy and Analytical Moments Accountant Yu-Xiang Wang Borja Balle S. Kasiviswanathan 14 398 0 31 Jul 2018
Differentially-Private "Draw and Discard" Machine Learning Vasyl Pihur Aleksandra Korolova Frederick Liu Subhash Sankuratripati M. Yung Dachuan Huang Ruogu Zeng FedML 33 39 0 11 Jul 2018
Privacy Amplification by Subsampling: Tight Analyses via Couplings and Divergences Borja Balle Gilles Barthe Marco Gaboardi 27 378 0 04 Jul 2018
The Right Complexity Measure in Locally Private Estimation: It is not the Fisher Information John C. Duchi Feng Ruan 23 50 0 14 Jun 2018
An end-to-end Differentially Private Latent Dirichlet Allocation Using a Spectral Algorithm Christopher DeCarolis Mukul Ram Seyed-Alireza Esmaeili Yu-Xiang Wang Furong Huang FedML 11 12 0 25 May 2018
Differentially Private Confidence Intervals for Empirical Risk Minimization Yue Wang Daniel Kifer Jaewoo Lee 21 33 0 11 Apr 2018
Privacy-preserving Prediction Cynthia Dwork Vitaly Feldman 25 90 0 27 Mar 2018
The Everlasting Database: Statistical Validity at a Fair Price Blake E. Woodworth Vitaly Feldman Saharon Rosset Nathan Srebro 32 2 0 12 Mar 2018
Scalable Private Learning with PATE Nicolas Papernot Shuang Song Ilya Mironov A. Raghunathan Kunal Talwar Ulfar Erlingsson 32 606 0 24 Feb 2018
Differentially Private Matrix Completion Revisited Prateek Jain Om Thakkar Abhradeep Thakurta FedML 26 34 0 28 Dec 2017
Calibrating Noise to Variance in Adaptive Data Analysis Vitaly Feldman Thomas Steinke 38 47 0 19 Dec 2017