Sample and Threshold Differential Privacy: Histograms and applications

10 December 2021

Papers citing "Sample and Threshold Differential Privacy: Histograms and applications"

11 / 11 papers shown

Title
Federated Heavy Hitter Analytics with Local Differential Privacy Yuemin Zhang Qingqing Ye Haibo Hu FedML 82 1 0 03 Jan 2025
Nebula: Efficient, Private and Accurate Histogram Estimation Ali Shahin Shamsabadi Peter Snyder Ralph Giles A. Bellet Hamed Haddadi 22 0 0 15 Sep 2024
A Survey on Federated Analytics: Taxonomy, Enabling Techniques, Applications and Open Issues Zibo Wang Haichao Ji Yifei Zhu Dan Wang Zhu Han 51 1 0 19 Apr 2024
PA-iMFL: Communication-Efficient Privacy Amplification Method against Data Reconstruction Attack in Improved Multi-Layer Federated Learning Jianhua Wang Xiaolin Chang Jelena Mivsić Vojislav B. Mivsić Zhi Chen Junchao Fan 43 2 0 25 Sep 2023
Samplable Anonymous Aggregation for Private Federated Data Analysis Kunal Talwar Shan Wang Audra McMillan Vojta Jina Vitaly Feldman ... Congzheng Song Karl Tarbe Sebastian Vogt L. Winstrom Shundong Zhou FedML 38 13 0 27 Jul 2023
Differentially Private Heavy Hitter Detection using Federated Analytics Karan N. Chadha Junye Chen John C. Duchi Vitaly Feldman H. Hashemi O. Javidbakht Audra McMillan Kunal Talwar FedML 27 7 0 21 Jul 2023
Privacy-Preserving Federated Heavy Hitter Analytics for Non-IID Data Jiaqi Shao Shanshan Han Chaoyang He B. Luo FedML 33 1 0 05 Jul 2023
CRS-FL: Conditional Random Sampling for Communication-Efficient and Privacy-Preserving Federated Learning Jianhua Wang Xiaolin Chang J. Misic Vojislav B. Mišić Lin Li Yingying Yao FedML 19 3 0 01 Jun 2023
Privacy Amplification via Compression: Achieving the Optimal Privacy-Accuracy-Communication Trade-off in Distributed Mean Estimation Wei-Ning Chen Danni Song Ayfer Özgür Peter Kairouz FedML 31 25 0 04 Apr 2023
Papaya: Practical, Private, and Scalable Federated Learning Dzmitry Huba John Nguyen Kshitiz Malik Ruiyu Zhu Michael G. Rabbat ... H. Srinivas Kaikai Wang Anthony Shoumikhin Jesik Min Mani Malek FedML 113 137 0 08 Nov 2021
Practical and Private (Deep) Learning without Sampling or Shuffling Peter Kairouz Brendan McMahan Shuang Song Om Thakkar Abhradeep Thakurta Zheng Xu FedML 182 154 0 26 Feb 2021