Concentrated Differential Privacy

6 March 2016

Papers citing "Concentrated Differential Privacy"

50 / 270 papers shown

Title
Widespread Underestimation of Sensitivity in Differentially Private Libraries and How to Fix It Sílvia Casacuberta Michael Shoemate Salil P. Vadhan Connor Wagaman 24 22 0 21 Jul 2022
Composition Theorems for Interactive Differential Privacy Xin Lyu 12 19 0 19 Jul 2022
Concurrent Composition Theorems for Differential Privacy Salil P. Vadhan Wanrong Zhang 14 16 0 18 Jul 2022
Faster Privacy Accounting via Evolving Discretization Badih Ghazi Pritish Kamath Ravi Kumar Pasin Manurangsi 65 14 0 10 Jul 2022
Shuffle Gaussian Mechanism for Differential Privacy Seng Pei Liew Tsubasa Takahashi FedML 29 2 0 20 Jun 2022
Private Synthetic Data with Hierarchical Structure Terrance Liu Zhiwei Steven Wu SyDa 24 3 0 13 Jun 2022
Analytical Composition of Differential Privacy via the Edgeworth Accountant Hua Wang Sheng-yang Gao Huanyu Zhang Milan Shen Weijie J. Su FedML 33 21 0 09 Jun 2022
Confidentiality Protection in the 2020 US Census of Population and Housing John M. Abowd Michael B. Hawes 19 26 0 07 Jun 2022
Privacy Amplification via Shuffled Check-Ins Seng Pei Liew Satoshi Hasegawa Tsubasa Takahashi FedML 32 0 0 07 Jun 2022
Offline Reinforcement Learning with Differential Privacy Dan Qiao Yu-Xiang Wang OffRL 39 23 0 02 Jun 2022
Data Augmentation MCMC for Bayesian Inference from Privatized Data Nianqiao P. Ju Jordan Awan Ruobin Gong Vinayak A. Rao 32 23 0 01 Jun 2022
Privacy of Noisy Stochastic Gradient Descent: More Iterations without More Privacy Loss Jason M. Altschuler Kunal Talwar FedML 36 57 0 27 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 24 1 0 06 May 2022
Privacy-Preserving Aggregation in Federated Learning: A Survey Ziyao Liu Jiale Guo Wenzhuo Yang Jiani Fan Kwok-Yan Lam Jun Zhao FedML 32 87 0 31 Mar 2022
Private Non-Convex Federated Learning Without a Trusted Server Andrew Lowy Ali Ghafelebashi Meisam Razaviyayn FedML 36 24 0 13 Mar 2022
Fully Adaptive Composition in Differential Privacy Justin Whitehouse Aaditya Ramdas Ryan M. Rogers Zhiwei Steven Wu 8 40 0 10 Mar 2022
Differential privacy for symmetric log-concave mechanisms S. Vinterbo 11 4 0 23 Feb 2022
Trusted AI in Multi-agent Systems: An Overview of Privacy and Security for Distributed Learning Chuan Ma Jun Li Kang Wei Bo Liu Ming Ding Long Yuan Zhu Han H. Vincent Poor 57 42 0 18 Feb 2022
Improved Differential Privacy for SGD via Optimal Private Linear Operators on Adaptive Streams S. Denisov H. B. McMahan J. Rush Adam D. Smith Abhradeep Thakurta FedML 33 60 0 16 Feb 2022
A Joint Exponential Mechanism For Differentially Private Top- $k$ Jennifer Gillenwater Matthew Joseph Andrés Munoz Medina Mónica Ribero 106 14 0 28 Jan 2022
Financial Vision Based Differential Privacy Applications Jun-Hao Chen Yi-Jen Wang Yun-Cheng Tsai Samuel Yen-Chi Chen FedML 21 1 0 28 Dec 2021
Robust and Privacy-Preserving Collaborative Learning: A Comprehensive Survey Shangwei Guo Xu Zhang Feiyu Yang Tianwei Zhang Yan Gan Tao Xiang Yang Liu FedML 31 9 0 19 Dec 2021
Are We There Yet? Timing and Floating-Point Attacks on Differential Privacy Systems Jiankai Jin Eleanor McMurtry Benjamin I. P. Rubinstein O. Ohrimenko 16 36 0 10 Dec 2021
Private and polynomial time algorithms for learning Gaussians and beyond H. Ashtiani Christopher Liaw 63 44 0 22 Nov 2021
Offset-Symmetric Gaussians for Differential Privacy Parastoo Sadeghi Mehdi Korki 18 8 0 13 Oct 2021
The Skellam Mechanism for Differentially Private Federated Learning Naman Agarwal Peter Kairouz Ziyu Liu FedML 22 122 0 11 Oct 2021
Hyperparameter Tuning with Renyi Differential Privacy Nicolas Papernot Thomas Steinke 135 120 0 07 Oct 2021
Towards General-purpose Infrastructure for Protecting Scientific Data Under Study Andrew Trask Kritika Prakash 41 3 0 04 Oct 2021
A unified interpretation of the Gaussian mechanism for differential privacy through the sensitivity index Georgios Kaissis Moritz Knolle F. Jungmann Alexander Ziller Dmitrii Usynin Daniel Rueckert 22 1 0 22 Sep 2021
The power of private likelihood-ratio tests for goodness-of-fit in frequency tables Emanuele Dolera Stefano Favaro 9 1 0 20 Sep 2021
Making the Most of Parallel Composition in Differential Privacy Joshua Smith Hassan Jameel Asghar Gianpaolo Gioiosa Sirine Mrabet Serge Gaspers P. Tyler 31 10 0 19 Sep 2021
Utility Fairness for the Differentially Private Federated Learning S. Alvi Yi Hong S. Durrani FedML 11 8 0 11 Sep 2021
Privacy-preserving Machine Learning for Medical Image Classification Shreyansh Singh K. Shukla 8 5 0 29 Aug 2021
Private Retrieval, Computing and Learning: Recent Progress and Future Challenges S. Ulukus Salman Avestimehr Michael C. Gastpar S. Jafar Ravi Tandon Chao Tian FedML 30 64 0 30 Jul 2021
Survey: Leakage and Privacy at Inference Time Marija Jegorova Chaitanya Kaul Charlie Mayor Alison Q. OÑeil Alexander Weir Roderick Murray-Smith Sotirios A. Tsaftaris PILM MIACV 21 71 0 04 Jul 2021
Smoothed Differential Privacy Ao Liu Yu-Xiang Wang Lirong Xia 33 0 0 04 Jul 2021
Covariance-Aware Private Mean Estimation Without Private Covariance Estimation Gavin Brown Marco Gaboardi Adam D. Smith Jonathan R. Ullman Lydia Zakynthinou FedML 28 48 0 24 Jun 2021
Generalization in the Face of Adaptivity: A Bayesian Perspective Moshe Shenfeld Katrina Ligett 19 4 0 20 Jun 2021
Privacy Amplification via Iteration for Shuffled and Online PNSGD Matteo Sordello Zhiqi Bu Jinshuo Dong FedML 11 7 0 20 Jun 2021
Some Examples of Privacy-preserving Publication and Sharing of COVID-19 Pandemic Data F. Liu Dong Wang Tian Yan 19 1 0 18 Jun 2021
Non-parametric Differentially Private Confidence Intervals for the Median Joerg Drechsler Ira Globus-Harris Audra McMillan Jayshree Sarathy Adam D. Smith 19 13 0 18 Jun 2021
Iterative Methods for Private Synthetic Data: Unifying Framework and New Methods Terrance Liu G. Vietri Zhiwei Steven Wu SyDa 33 61 0 14 Jun 2021
Numerical Composition of Differential Privacy Sivakanth Gopi Y. Lee Lukas Wutschitz 14 173 0 05 Jun 2021
Concurrent Composition of Differential Privacy Salil P. Vadhan Tianhao Wang 11 20 0 30 May 2021
Oneshot Differentially Private Top-k Selection Gang Qiao Weijie J. Su Li Zhang 13 31 0 18 May 2021
On the Renyi Differential Privacy of the Shuffle Model Antonious M. Girgis Deepesh Data Suhas Diggavi A. Suresh Peter Kairouz 22 44 0 11 May 2021
Channels of Small Log-Ratio Leakage and Characterization of Two-Party Differentially Private Computation Iftach Haitner N. Mazor Ronen Shaltiel Jad Silbak FedML 20 11 0 03 May 2021
Improved Matrix Gaussian Mechanism for Differential Privacy Jungang Yang Liyao Xiang Weiting Li Wei Liu Xinbing Wang 13 5 0 30 Apr 2021
Super-convergence and Differential Privacy: Training faster with better privacy guarantees Osvald Frisk Friedrich Dörmann Christian Marius Lillelund Christian Fischer Pedersen FedML 11 2 0 18 Mar 2021
Quantifying identifiability to choose and audit $ε$ in differentially private deep learning Daniel Bernau Günther Eibl Philip-William Grassal Hannah Keller Florian Kerschbaum FedML 14 5 0 04 Mar 2021