Concentrated Differential Privacy

6 March 2016

Papers citing "Concentrated Differential Privacy"

50 / 270 papers shown

Title
Privacy Amplification of Iterative Algorithms via Contraction Coefficients S. Asoodeh Mario Díaz Flavio du Pin Calmon FedML 13 17 0 17 Jan 2020
Element Level Differential Privacy: The Right Granularity of Privacy Hilal Asi John C. Duchi O. Javidbakht 11 18 0 05 Dec 2019
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
Deep Learning with Gaussian Differential Privacy Zhiqi Bu Jinshuo Dong Qi Long Weijie J. Su FedML 14 205 0 26 Nov 2019
Federated Learning with Bayesian Differential Privacy Aleksei Triastcyn Boi Faltings FedML 19 172 0 22 Nov 2019
Proximal Langevin Algorithm: Rapid Convergence Under Isoperimetry Andre Wibisono 72 49 0 04 Nov 2019
Composition Properties of Bayesian Differential Privacy Jun Zhao 10 1 0 02 Nov 2019
Relations among different privacy notions Jun Zhao 8 1 0 02 Nov 2019
Obfuscation via Information Density Estimation Hsiang Hsu S. Asoodeh Flavio du Pin Calmon 20 12 0 17 Oct 2019
Information-theoretic metrics for Local Differential Privacy protocols Milan Lopuhaä-Zwakenberg B. Škorić Ninghui Li 17 15 0 17 Oct 2019
Exact Inference with Approximate Computation for Differentially Private Data via Perturbations Ruobin Gong 29 25 0 26 Sep 2019
A Programming Framework for Differential Privacy with Accuracy Concentration Bounds Elisabet Lobo Vesga Alejandro Russo Marco Gaboardi 12 29 0 10 Sep 2019
Rényi Differential Privacy of the Sampled Gaussian Mechanism Ilya Mironov Kunal Talwar Li Zhang 14 277 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 Distribution Obfuscation via Probability Coupling Yusuke Kawamoto Takao Murakami 30 7 0 13 Jul 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
The Cost of a Reductions Approach to Private Fair Optimization Daniel Alabi 41 3 0 23 Jun 2019
A unified view on differential privacy and robustness to adversarial examples Rafael Pinot Florian Yger Cédric Gouy-Pailler Jamal Atif AAML 19 17 0 19 Jun 2019
Average-Case Averages: Private Algorithms for Smooth Sensitivity and Mean Estimation Mark Bun Thomas Steinke 47 74 0 06 Jun 2019
SoK: Differential Privacies Damien Desfontaines Balázs Pejó 33 122 0 04 Jun 2019
Private Hypothesis Selection Mark Bun Gautam Kamath Thomas Steinke Zhiwei Steven Wu 12 89 0 30 May 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
Hypothesis Testing Interpretations and Renyi Differential Privacy Borja Balle Gilles Barthe Marco Gaboardi Justin Hsu Tetsuya Sato 9 108 0 24 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
Differentially Private Model Publishing for Deep Learning Lei Yu Ling Liu C. Pu Mehmet Emre Gursoy Stacey Truex FedML 15 263 0 03 Apr 2019
Differentially Private Inference for Binomial Data Jordan Awan Aleksandra B. Slavkovic 12 24 0 31 Mar 2019
Rapid Convergence of the Unadjusted Langevin Algorithm: Isoperimetry Suffices Santosh Vempala Andre Wibisono 23 260 0 20 Mar 2019
Evaluating Differentially Private Machine Learning in Practice Bargav Jayaraman David E. Evans 15 7 0 24 Feb 2019
Averaging Attacks on Bounded Noise-based Disclosure Control Algorithms Hassan Jameel Asghar Dali Kaafar AAML 17 10 0 18 Feb 2019
The Cost of Privacy: Optimal Rates of Convergence for Parameter Estimation with Differential Privacy T. Tony Cai Yichen Wang Linjun Zhang 38 162 0 12 Feb 2019
Lower Bounds for Locally Private Estimation via Communication Complexity John C. Duchi Ryan M. Rogers 13 93 0 01 Feb 2019
Privacy Preserving Off-Policy Evaluation Tengyang Xie Philip S. Thomas G. Miklau OffRL 14 4 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
Bayesian Differential Privacy for Machine Learning Aleksei Triastcyn Boi Faltings 28 2 0 28 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
Differential Privacy Techniques for Cyber Physical Systems: A Survey M. Hassan M. H. Rehmani Jinjun Chen 19 432 0 06 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 18 357 0 03 Dec 2018
The Structure of Optimal Private Tests for Simple Hypotheses C. Canonne Gautam Kamath Audra McMillan Adam D. Smith Jonathan R. Ullman 21 71 0 27 Nov 2018
Privacy Amplification by Iteration Vitaly Feldman Ilya Mironov Kunal Talwar Abhradeep Thakurta FedML 18 170 0 20 Aug 2018
Subsampled Rényi Differential Privacy and Analytical Moments Accountant Yu-Xiang Wang Borja Balle S. Kasiviswanathan 14 397 0 31 Jul 2018
Differentially Private False Discovery Rate Control Cynthia Dwork Weijie J. Su Li Zhang 20 23 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
User's Privacy in Recommendation Systems Applying Online Social Network Data, A Survey and Taxonomy E. Aghasian Saurabh Garg James Montgomery OffRL 6 15 0 20 Jun 2018
Property Testing for Differential Privacy A. Gilbert Audra McMillan 11 27 0 17 Jun 2018
The Right Complexity Measure in Locally Private Estimation: It is not the Fisher Information John C. Duchi Feng Ruan 17 50 0 14 Jun 2018
Detecting Violations of Differential Privacy Zeyu Ding Yuxin Wang Guanhong Wang Danfeng Zhang Daniel Kifer 14 135 0 25 May 2018
Improving the Gaussian Mechanism for Differential Privacy: Analytical Calibration and Optimal Denoising Borja Balle Yu-Xiang Wang MLT 13 389 0 16 May 2018
Privately Learning High-Dimensional Distributions Gautam Kamath Jerry Li Vikrant Singhal Jonathan R. Ullman FedML 72 148 0 01 May 2018
Generating Artificial Data for Private Deep Learning Aleksei Triastcyn Boi Faltings 21 48 0 08 Mar 2018