Empirical Risk Minimization in the Non-interactive Local Model of Differential Privacy

Di Wang, Marco Gaboardi, Adam Smith, Jinhui Xu

Type: Preprint

Publication Date: 2020-01-01

Citations: 2

DOI: https://doi.org/10.48550/arxiv.2011.05934

View Publication

Locations

arXiv (Cornell University) - View
DataCite API - View

Similar Works

Action	Title	Year	Authors
+	Empirical Risk Minimization in the Non-interactive Local Model of Differential Privacy	2020	Di Wang Marco Gaboardi Adam Smith Jinhui Xu
+ PDF Chat	Empirical Risk Minimization in the Non-interactive Local Model of Differential Privacy	2020	Di Wang Marco Gaboardi Adam Smith Jinhui Xu
+	Empirical Risk Minimization in Non-interactive Local Differential Privacy: Efficiency and High Dimensional Case	2018	Di Wang Marco Gaboardi Jinhui Xu
+	Differentially Private Empirical Risk Minimization in Non-interactive Local Model via Polynomial of Inner Product Approximation.	2018	Di Wang Adam Smith Jinhui Xu
+	Noninteractive Locally Private Learning of Linear Models via Polynomial Approximations	2018	Di Wang Adam Smith Jinhui Xu
+	Noninteractive Locally Private Learning of Linear Models via Polynomial Approximations	2018	Di Wang Adam Smith Jinhui Xu
+	Locally differentially private estimation of nonlinear functionals of discrete distributions	2021	Cristina Butucea Yann Issartel
+	Locally differentially private estimation of nonlinear functionals of discrete distributions	2021	Cristina Butucea Yann Issartel
+	Estimating Smooth GLM in Non-interactive Local Differential Privacy Model with Public Unlabeled Data	2019	Di Wang Lijie Hu Huanyu Zhang Marco Gaboardi Jinhui Xu
+	Interactive versus non-interactive locally differentially private estimation: Two elbows for the quadratic functional	2020	Cristina Butucea Angelika Rohde Lukas Steinberger
+ PDF Chat	Private Convex Optimization via Exponential Mechanism	2024	Sivakanth Gopi Yin Tat Lee Daogao Liu
+	Collect at Once, Use Effectively: Making Non-interactive Locally Private Learning Possible	2017	Kai Zheng Wenlong Mou Liwei Wang
+	Private Convex Optimization via Exponential Mechanism	2022	Sivakanth Gopi Yin Tat Lee Daogao Liu
+	Improved Analysis of Sparse Linear Regression in Local Differential Privacy Model	2023	Liyang Zhu Meng Ding Vaneet Aggarwal Jinhui Xu Di Wang
+	Differentially Private Non-Convex Optimization under the KL Condition with Optimal Rates	2023	Michael Menart Enayat Ullah Raman Arora Raef Bassily Cristóbal Guzmán
+	Estimating Smooth GLM in Non-interactive Local Differential Privacy Model with Public Unlabeled Data	2019	Di Wang Lijie Hu Huanyu Zhang Marco Gaboardi Jinhui Xu
+ PDF Chat	Interactive versus noninteractive locally differentially private estimation: Two elbows for the quadratic functional	2023	Cristina Butucea Angelika Rohde Lukas Steinberger
+	Differentially Private Empirical Risk Minimization: Efficient Algorithms and Tight Error Bounds	2014	Raef Bassily Adam Smith Abhradeep Thakurta
+ PDF Chat	Contraction of Locally Differentially Private Mechanisms	2024	Shahab Asoodeh Huanyu Zhang
+	Interaction is necessary for distributed learning with privacy or communication constraints	2019	Yuval Dagan Vitaly Feldman

Works That Cite This (2)

Action	Title	Year	Authors
+	Faster Rates of Differentially Private Stochastic Convex Optimization.	2021	Jinyan Su Di Wang
+	High Dimensional Differentially Private Stochastic Optimization with Heavy-tailed Data	2022	Lijie Hu Shuo Ni Hanshen Xiao Di Wang

Works Cited by This (0)

Action	Title	Year	Authors