Empirical Risk Minimization in Non-interactive Local Differential Privacy: Efficiency and High Dimensional Case

12 February 2018

Papers citing "Empirical Risk Minimization in Non-interactive Local Differential Privacy: Efficiency and High Dimensional Case"

13 / 13 papers shown

Title
Bipartite Randomized Response Mechanism for Local Differential Privacy Shun Zhang Hai Zhu Zhili Chen N. Xiong 41 0 0 29 Apr 2025
Distributed Differentially Private Data Analytics via Secure Sketching Jakob Burkhardt Hannah Keller Claudio Orlandi Chris Schwiegelshohn FedML 82 0 0 30 Nov 2024
On the Fairness Impacts of Private Ensembles Models Cuong Tran Ferdinando Fioretto 41 4 0 19 May 2023
Privacy Amplification via Shuffling: Unified, Simplified, and Tightened Shaowei Wang FedML 26 9 0 11 Apr 2023
Differentially Private Natural Language Models: Recent Advances and Future Directions Lijie Hu Ivan Habernal Lei Shen Di Wang AAML 35 18 0 22 Jan 2023
On PAC Learning Halfspaces in Non-interactive Local Privacy Model with Public Unlabeled Data Jinyan Su Jinhui Xu Di Wang 21 2 0 17 Sep 2022
Practical Vertical Federated Learning with Unsupervised Representation Learning Zhaomin Wu Yue Liu Bingsheng He FedML 38 37 0 13 Aug 2022
One-bit Submission for Locally Private Quasi-MLE: Its Asymptotic Normality and Limitation Hajime Ono Kazuhiro Minami H. Hino 16 0 0 15 Feb 2022
Privacy Amplification by Decentralization Edwige Cyffers A. Bellet FedML 49 39 0 09 Dec 2020
On Differentially Private Stochastic Convex Optimization with Heavy-tailed Data Di Wang Hanshen Xiao S. Devadas Jinhui Xu 29 55 0 21 Oct 2020
Input Perturbation: A New Paradigm between Central and Local Differential Privacy Yilin Kang Yong Liu Ben Niu Xin-Yi Tong Likun Zhang Weiping Wang 27 11 0 20 Feb 2020
Wireless Federated Learning with Local Differential Privacy Mohamed Seif Ravi Tandon Ming Li 84 171 0 12 Feb 2020
Locally Differentially Private Data Collection and Analysis Teng Wang Jun Zhao Xinyu Yang Xuebin Ren 27 13 0 05 Jun 2019