Stronger Privacy Amplification by Shuffling for Rényi and Approximate Differential Privacy

9 August 2022

Papers citing "Stronger Privacy Amplification by Shuffling for Rényi and Approximate Differential Privacy"

30 / 30 papers shown

Title
Leveraging Randomness in Model and Data Partitioning for Privacy Amplification Andy Dong Wei-Ning Chen Ayfer Özgür FedML 54 1 0 04 Mar 2025
Learning from End User Data with Shuffled Differential Privacy over Kernel Densities Tal Wagner FedML 50 0 0 21 Feb 2025
Segmented Private Data Aggregation in the Multi-message Shuffle Model Shaowei Wang Hongqiao Chen Sufen Zeng Ruilin Yang Hui Jiang ... Kaiqi Yu Rundong Mei Shaozheng Huang Wei Yang Bangzhou Xin FedML 54 0 0 31 Dec 2024
When Focus Enhances Utility: Target Range LDP Frequency Estimation and Unknown Item Discovery Bo Jiang Wanrong Zhang Donghang Lu Jian Du Qiang Yan 26 0 0 23 Dec 2024
Scalable DP-SGD: Shuffling vs. Poisson Subsampling Lynn Chua Badih Ghazi Pritish Kamath Ravi Kumar Pasin Manurangsi Amer Sinha Chiyuan Zhang 36 5 0 06 Nov 2024
A Statistical Viewpoint on Differential Privacy: Hypothesis Testing, Representation and Blackwell's Theorem Weijie J. Su 31 1 0 14 Sep 2024
Enhanced Privacy Bound for Shuffle Model with Personalized Privacy Yi-xiao Liu Yuhan Liu Li Xiong Yujie Gu Hong Chen FedML 37 0 0 25 Jul 2024
Universally Harmonizing Differential Privacy Mechanisms for Federated Learning: Boosting Accuracy and Convergence Shuya Feng Meisam Mohammady Hanbin Hong Shenao Yan Ashish Kundu Binghui Wang Yuan Hong FedML 38 3 0 20 Jul 2024
Beyond Statistical Estimation: Differentially Private Individual Computation via Shuffling Shaowei Wang Changyu Dong Xiangfu Song Jin Li Zhili Zhou Di Wang Han Wu 41 0 0 26 Jun 2024
Click Without Compromise: Online Advertising Measurement via Per User Differential Privacy Yingtai Xiao Jian Du Shikun Zhang Qiang Yan Danfeng Zhang Daniel Kifer Daniel Kifer 49 2 0 04 Jun 2024
Improved Communication-Privacy Trade-offs in $L_2$ Mean Estimation under Streaming Differential Privacy Wei-Ning Chen Berivan Isik Peter Kairouz Albert No Sewoong Oh Zheng Xu 47 3 0 02 May 2024
How Private are DP-SGD Implementations? Lynn Chua Badih Ghazi Pritish Kamath Ravi Kumar Pasin Manurangsi Amer Sinha Chiyuan Zhang 37 12 0 26 Mar 2024
Unified Enhancement of Privacy Bounds for Mixture Mechanisms via $f$ -Differential Privacy Chendi Wang Buxin Su Jiayuan Ye Reza Shokri Weijie J. Su FedML 11 10 0 30 Oct 2023
Differentially Private Aggregation via Imperfect Shuffling Badih Ghazi Ravi Kumar Pasin Manurangsi Jelani Nelson Samson Zhou FedML 30 1 0 28 Aug 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 17 7 0 21 Jul 2023
Training generative models from privatized data Daria Reshetova Wei-Ning Chen Ayfer Özgür FedML 20 2 0 15 Jun 2023
Amplification by Shuffling without Shuffling Borja Balle James Bell Adria Gascon FedML 32 2 0 18 May 2023
Privacy Amplification via Shuffling: Unified, Simplified, and Tightened Shaowei Wang FedML 26 9 0 11 Apr 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 15 25 0 04 Apr 2023
Multi-Message Shuffled Privacy in Federated Learning Antonious M. Girgis Suhas Diggavi FedML 20 8 0 22 Feb 2023
One-shot Empirical Privacy Estimation for Federated Learning Galen Andrew Peter Kairouz Sewoong Oh Alina Oprea H. B. McMahan Vinith M. Suriyakumar FedML 21 32 0 06 Feb 2023
Lemmas of Differential Privacy Yiyang Huang C. Canonne 29 1 0 21 Nov 2022
Private Federated Statistics in an Interactive Setting Audra McMillan O. Javidbakht Kunal Talwar Elliot Briggs Mike Chatzidakis ... Paul J. Pelzl Rehan Rishi Congzheng Song Shan Wang Shundong Zhou FedML 19 6 0 18 Nov 2022
Composition of Differential Privacy & Privacy Amplification by Subsampling Thomas Steinke 56 49 0 02 Oct 2022
Individual Privacy Accounting with Gaussian Differential Privacy A. Koskela Marlon Tobaben Antti Honkela 34 18 0 30 Sep 2022
Individual Privacy Accounting for Differentially Private Stochastic Gradient Descent Da Yu Gautam Kamath Janardhan Kulkarni Tie-Yan Liu Jian Yin Huishuai Zhang 11 17 0 06 Jun 2022
Differentially Private Learning Needs Hidden State (Or Much Faster Convergence) Jiayuan Ye Reza Shokri FedML 22 44 0 10 Mar 2022
Private Aggregation from Fewer Anonymous Messages Badih Ghazi Pasin Manurangsi Rasmus Pagh A. Velingker FedML 42 55 0 24 Sep 2019
Amplification by Shuffling: From Local to Central Differential Privacy via Anonymity Ulfar Erlingsson Vitaly Feldman Ilya Mironov A. Raghunathan Kunal Talwar Abhradeep Thakurta 141 420 0 29 Nov 2018
Prochlo: Strong Privacy for Analytics in the Crowd Andrea Bittau Ulfar Erlingsson Petros Maniatis Ilya Mironov A. Raghunathan David Lie Mitch Rudominer Ushasree Kode J. Tinnés B. Seefeld 88 278 0 02 Oct 2017