Learning with User-Level Local Differential Privacy

Learning with User-Level Local Differential Privacy

27 May 2024

Huiwen Wu

Papers citing "Learning with User-Level Local Differential Privacy"

17 / 17 papers shown

Title
User-level Differentially Private Stochastic Convex Optimization: Efficient Algorithms with Optimal Rates Hilal Asi Daogao Liu 48 11 0 07 Nov 2023
A Huber Loss Minimization Approach to Byzantine Robust Federated Learning Puning Zhao Fei Yu Zhiguo Wan FedML 89 14 0 24 Aug 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 51 26 0 04 Apr 2023
Stability is Stable: Connections between Replicability, Privacy, and Adaptive Generalization Mark Bun Marco Gaboardi Max Hopkins R. Impagliazzo Rex Lei T. Pitassi Satchit Sivakumar Jessica Sorrell 54 29 0 22 Mar 2023
Discrete Distribution Estimation under User-level Local Differential Privacy Jayadev Acharya Yuhan Liu Ziteng Sun 55 16 0 07 Nov 2022
On robustness and local differential privacy Mengchu Li Thomas B. Berrett Yi Yu 42 26 0 03 Jan 2022
Instance-optimal Mean Estimation Under Differential Privacy Ziyue Huang Yuting Liang K. Yi 41 57 0 01 Jun 2021
Learning with User-Level Privacy Daniel Levy Ziteng Sun Kareem Amin Satyen Kale Alex Kulesza M. Mohri A. Suresh FedML 51 90 0 23 Feb 2021
Robust and Differentially Private Mean Estimation Xiyang Liu Weihao Kong Sham Kakade Sewoong Oh OOD FedML 66 77 0 18 Feb 2021
Strongly universally consistent nonparametric regression and classification with privatised data Thomas B. Berrett László Gyorfi Harro Walk 27 16 0 31 Oct 2020
Local Differential Privacy and Its Applications: A Comprehensive Survey Mengmeng Yang Lingjuan Lyu Jun Zhao Tianqing Zhu Kwok-Yan Lam 65 145 0 09 Aug 2020
Advances and Open Problems in Federated Learning Peter Kairouz H. B. McMahan Brendan Avent A. Bellet M. Bennis ... Zheng Xu Qiang Yang Felix X. Yu Han Yu Sen Zhao FedML AI4CE 212 6,229 0 10 Dec 2019
Federated Learning with Differential Privacy: Algorithms and Performance Analysis Kang Wei Jun Li Ming Ding Chuan Ma Heng Yang Farokhi Farhad Shi Jin Tony Q.S. Quek H. Vincent Poor FedML 110 1,612 0 01 Nov 2019
Private Stochastic Convex Optimization with Optimal Rates Raef Bassily Vitaly Feldman Kunal Talwar Abhradeep Thakurta 65 241 0 27 Aug 2019
Average-Case Averages: Private Algorithms for Smooth Sensitivity and Mean Estimation Mark Bun Thomas Steinke 63 75 0 06 Jun 2019
Deep Learning with Differential Privacy Martín Abadi Andy Chu Ian Goodfellow H. B. McMahan Ilya Mironov Kunal Talwar Li Zhang FedML SyDa 191 6,109 0 01 Jul 2016
Fast learning rates for plug-in classifiers Jean-Yves Audibert Alexandre B. Tsybakov 528 465 0 17 Aug 2007