Beyond Statistical Estimation: Differentially Private Individual Computation via Shuffling

26 June 2024

Papers citing "Beyond Statistical Estimation: Differentially Private Individual Computation via Shuffling"

31 / 31 papers shown

Title
Private Means and the Curious Incident of the Free Lunch Jack Fitzsimons James Honaker Michael Shoemate Vikrant Singhal 63 2 0 19 Aug 2024
Better Gaussian Mechanism using Correlated Noise Christian Janos Lebeda 73 3 0 13 Aug 2024
Feature Inference Attack on Shapley Values Xinjian Luo Yangfan Jiang X. Xiao AAML FAtt 62 19 0 16 Jul 2024
Private Vector Mean Estimation in the Shuffle Model: Optimal Rates Require Many Messages Hilal Asi Vitaly Feldman Jelani Nelson Huy Le Nguyen Kunal Talwar Samson Zhou FedML 55 5 0 16 Apr 2024
Exact Optimality of Communication-Privacy-Utility Tradeoffs in Distributed Mean Estimation Berivan Isik Wei-Ning Chen Ayfer Özgür Tsachy Weissman Albert No 92 19 0 08 Jun 2023
Fast Optimal Locally Private Mean Estimation via Random Projections Hilal Asi Vitaly Feldman Jelani Nelson Huy Le Nguyen Kunal Talwar FedML 55 14 0 07 Jun 2023
Privacy Amplification via Shuffling: Unified, Simplified, and Tightened Shaowei Wang FedML 67 9 0 11 Apr 2023
Stronger Privacy Amplification by Shuffling for Rényi and Approximate Differential Privacy Vitaly Feldman Audra McMillan Kunal Talwar FedML 72 49 0 09 Aug 2022
Optimal Algorithms for Mean Estimation under Local Differential Privacy Hilal Asi Vitaly Feldman Kunal Talwar 76 41 0 05 May 2022
Optimal Compression of Locally Differentially Private Mechanisms Abhin Shah Wei-Ning Chen Johannes Ballé Peter Kairouz Lucas Theis 60 42 0 29 Oct 2021
Differentially Private Aggregation in the Shuffle Model: Almost Central Accuracy in Almost a Single Message Badih Ghazi Ravi Kumar Pasin Manurangsi Rasmus Pagh Amer Sinha FedML 82 36 0 27 Sep 2021
Private Counting from Anonymous Messages: Near-Optimal Accuracy with Vanishing Communication Overhead Badih Ghazi Ravi Kumar Pasin Manurangsi Rasmus Pagh FedML 54 49 0 08 Jun 2021
Lossless Compression of Efficient Private Local Randomizers Vitaly Feldman Kunal Talwar 51 40 0 24 Feb 2021
Hiding Among the Clones: A Simple and Nearly Optimal Analysis of Privacy Amplification by Shuffling Vitaly Feldman Audra McMillan Kunal Talwar FedML 59 161 0 23 Dec 2020
On the Round Complexity of the Shuffle Model A. Beimel Iftach Haitner Kobbi Nissim Uri Stemmer FedML 78 15 0 28 Sep 2020
Breaking the Communication-Privacy-Accuracy Trilemma Wei-Ning Chen Peter Kairouz Ayfer Özgür 102 119 0 22 Jul 2020
FedSel: Federated SGD under Local Differential Privacy with Top-k Dimension Selection Ruixuan Liu Yang Cao Masatoshi Yoshikawa Hong Chen FedML 39 108 0 24 Mar 2020
Estimating Numerical Distributions under Local Differential Privacy Zitao Li Tianhao Wang Milan Lopuhaä-Zwakenberg B. Škorić Ninghui Li 41 87 0 02 Dec 2019
Collecting and Analyzing Multidimensional Data with Local Differential Privacy Ning Wang Xiaokui Xiao Yifan Yang Jun Zhao S. Hui Hyejin Shin Junbum Shin Ge Yu 40 320 0 28 Jun 2019
The Privacy Blanket of the Shuffle Model Borja Balle James Bell Adria Gascon Kobbi Nissim FedML 61 237 0 07 Mar 2019
Lower Bounds for Locally Private Estimation via Communication Complexity John C. Duchi Ryan M. Rogers 48 93 0 01 Feb 2019
Protection Against Reconstruction and Its Applications in Private Federated Learning Abhishek Bhowmick John C. Duchi Julien Freudiger Gaurav Kapoor Ryan M. Rogers FedML 75 360 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 172 426 0 29 Nov 2018
Distributed Differential Privacy via Shuffling Albert Cheu Adam D. Smith Jonathan R. Ullman David Zeber M. Zhilyaev FedML 83 352 0 04 Aug 2018
Collecting Telemetry Data Privately Bolin Ding Janardhan Kulkarni Sergey Yekhanin 46 683 0 05 Dec 2017
Privacy Loss in Apple's Implementation of Differential Privacy on MacOS 10.12 Jun Tang Aleksandra Korolova Xiaolong Bai Xueqiang Wang Xiaofeng Wang 35 289 0 08 Sep 2017
Minimax Optimal Procedures for Locally Private Estimation John C. Duchi Martin J. Wainwright Michael I. Jordan 68 435 0 08 Apr 2016
Double or Nothing: Multiplicative Incentive Mechanisms for Crowdsourcing Nihar B. Shah Dengyong Zhou FedML 59 108 0 06 Aug 2014
RAPPOR: Randomized Aggregatable Privacy-Preserving Ordinal Response Ulfar Erlingsson Vasyl Pihur Aleksandra Korolova 86 1,987 0 25 Jul 2014
Geo-Indistinguishability: Differential Privacy for Location-Based Systems M. Andrés N. E. Bordenabe K. Chatzikokolakis C. Palamidessi 71 1,182 0 10 Dec 2012
What Can We Learn Privately? S. Kasiviswanathan Homin K. Lee Kobbi Nissim Sofya Raskhodnikova Adam D. Smith 115 1,465 0 06 Mar 2008