The Cost of Privacy: Optimal Rates of Convergence for Parameter
Estimation with Differential Privacy

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The Cost of Privacy: Optimal Rates of Convergence for Parameter Estimation with Differential Privacy

12 February 2019

T. Tony Cai

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Papers citing "The Cost of Privacy: Optimal Rates of Convergence for Parameter Estimation with Differential Privacy"

11 / 111 papers shown

Title
Median regression with differential privacy E. Chen Ying Miao Yu Tang 14 2 0 04 Jun 2020
A Primer on Private Statistics Gautam Kamath Jonathan R. Ullman 107 48 0 30 Apr 2020
Differentially Private Assouad, Fano, and Le Cam Jayadev Acharya Ziteng Sun Huanyu Zhang FedML 81 60 0 14 Apr 2020
Interactive versus non-interactive locally differentially private estimation: Two elbows for the quadratic functional C. Butucea Angelika Rohde Lukas Steinberger 82 14 0 10 Mar 2020
Private Mean Estimation of Heavy-Tailed Distributions Gautam Kamath Vikrant Singhal Jonathan R. Ullman 105 99 0 21 Feb 2020
Privately Learning Markov Random Fields Huanyu Zhang Gautam Kamath Janardhan Kulkarni Zhiwei Steven Wu 79 25 0 21 Feb 2020
Propose, Test, Release: Differentially private estimation with high probability Victor-Emmanuel Brunel Marco Avella-Medina FedML 67 22 0 19 Feb 2020
Differentially private sub-Gaussian location estimators Marco Avella-Medina Victor-Emmanuel Brunel 52 18 0 27 Jun 2019
Private Hypothesis Selection Mark Bun Gautam Kamath Thomas Steinke Zhiwei Steven Wu 87 91 0 30 May 2019
Private Identity Testing for High-Dimensional Distributions C. Canonne Gautam Kamath Audra McMillan Jonathan R. Ullman Lydia Zakynthinou 116 38 0 28 May 2019
Privately Learning High-Dimensional Distributions Gautam Kamath Jerry Li Vikrant Singhal Jonathan R. Ullman FedML 109 150 0 01 May 2018