Accuracy First: Selecting a Differential Privacy Level for
Accuracy-Constrained ERM

Accuracy First: Selecting a Differential Privacy Level for Accuracy-Constrained ERM

30 May 2017

Zhiwei Steven Wu

Papers citing "Accuracy First: Selecting a Differential Privacy Level for Accuracy-Constrained ERM"

17 / 17 papers shown

Title
Private Count Release: A Simple and Scalable Approach for Private Data Analytics Ryan Rogers 43 0 0 08 Mar 2024
Privacy Guarantees for Personal Mobility Data in Humanitarian Response Nitin Kohli Emily L. Aiken J. Blumenstock 24 7 0 15 Jun 2023
Unbounded Differentially Private Quantile and Maximum Estimation D. Durfee 56 6 0 02 May 2023
Bounding Training Data Reconstruction in DP-SGD Jamie Hayes Saeed Mahloujifar Borja Balle AAML FedML 40 39 0 14 Feb 2023
Answering Private Linear Queries Adaptively using the Common Mechanism Yingtai Xiao Guanhong Wang Danfeng Zhang Daniel Kifer 70 7 0 30 Nov 2022
Privacy-preserving Non-negative Matrix Factorization with Outliers Swapnil Saha H. Imtiaz PICV 21 3 0 02 Nov 2022
Brownian Noise Reduction: Maximizing Privacy Subject to Accuracy Constraints Justin Whitehouse Zhiwei Steven Wu Aaditya Ramdas Ryan M. Rogers 16 9 0 15 Jun 2022
$Privacy accounting $\varepsilon$conomics: Improving differential privacy composition via a posteriori bounds$ Privacy accounting $\varepsilon$ conomics: Improving differential privacy composition via a posteriori bounds Valentin Hartmann Vincent Bindschaedler Alexander Bentkamp Robert West 29 1 0 06 May 2022
Privately Publishable Per-instance Privacy Rachel Redberg Yu Wang 37 17 0 03 Nov 2021
Free Gap Estimates from the Exponential Mechanism, Sparse Vector, Noisy Max and Related Algorithms Zeyu Ding Yuxin Wang Yingtai Xiao Guanhong Wang Danfeng Zhang Daniel Kifer 31 6 0 02 Dec 2020
Deciding Accuracy of Differential Privacy Schemes Gilles Barthe Rohit Chadha Paul Krogmeier A. Sistla Mahesh Viswanathan 35 10 0 12 Nov 2020
The Sparse Vector Technique, Revisited Haim Kaplan Yishay Mansour Uri Stemmer 43 17 0 02 Oct 2020
Improved Differentially Private Decentralized Source Separation for fMRI Data H. Imtiaz Jafar Mohammadi Rogers F. Silva Bradley T. Baker Sergey Plis Anand D. Sarwate Vince D. Calhoun OOD 18 5 0 28 Oct 2019
Synthetic Data for Deep Learning Sergey I. Nikolenko 46 348 0 25 Sep 2019
Private PAC learning implies finite Littlestone dimension N. Alon Roi Livni M. Malliaris Shay Moran 23 110 0 04 Jun 2018
Differentially Private Confidence Intervals for Empirical Risk Minimization Yue Wang Daniel Kifer Jaewoo Lee 27 33 0 11 Apr 2018
Local Differential Privacy for Evolving Data Matthew Joseph Aaron Roth Jonathan R. Ullman Bo Waggoner 60 86 0 20 Feb 2018