Practical Differentially Private Top-$k$ Selection with Pay-what-you-get
Composition

Practical Differentially Private Top- $k$ Selection with Pay-what-you-get Composition

10 May 2019

Papers citing "Practical Differentially Private Top-$k$ Selection with Pay-what-you-get Composition"

18 / 18 papers shown

Title
Fast networked data selection via distributed smoothed quantile estimation Xu Zhang Marcos M. Vasconcelos 33 0 0 04 Jun 2024
Private Count Release: A Simple and Scalable Approach for Private Data Analytics Ryan Rogers 43 0 0 08 Mar 2024
Hot PATE: Private Aggregation of Distributions for Diverse Task Edith Cohen Benjamin Cohen-Wang Xin Lyu Jelani Nelson Tamas Sarlos Uri Stemmer 52 3 0 04 Dec 2023
DP-OPT: Make Large Language Model Your Privacy-Preserving Prompt Engineer Junyuan Hong Jiachen T. Wang Chenhui Zhang Zhangheng Li Bo-wen Li Zhangyang Wang 48 29 0 27 Nov 2023
Unbounded Differentially Private Quantile and Maximum Estimation D. Durfee 51 6 0 02 May 2023
Tight Data Access Bounds for Private Top- $k$ Selection Hao Wu O. Ohrimenko Anthony Wirth 13 0 0 31 Jan 2023
On the Choice of Databases in Differential Privacy Composition Valentin Hartmann Vincent Bindschaedler Robert West 34 0 0 27 Sep 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 24 1 0 06 May 2022
Adaptive Private-K-Selection with Adaptive K and Application to Multi-label PATE Yuqing Zhu Yu-Xiang Wang 35 18 0 30 Mar 2022
Exact Privacy Analysis of the Gaussian Sparse Histogram Mechanism Brian Karrer Daniel Kifer Arjun S. Wilkins Danfeng Zhang 20 4 0 02 Feb 2022
Differentially Private Top-k Selection via Canonical Lipschitz Mechanism Michael Shekelyan Grigorios Loukides 25 4 0 31 Jan 2022
The Price of Differential Privacy under Continual Observation Palak Jain Sofya Raskhodnikova Satchit Sivakumar Adam D. Smith 31 51 0 01 Dec 2021
Distribution-Invariant Differential Privacy Xuan Bi Xiaotong Shen 18 13 0 08 Nov 2021
Covariance-Aware Private Mean Estimation Without Private Covariance Estimation Gavin Brown Marco Gaboardi Adam D. Smith Jonathan R. Ullman Lydia Zakynthinou FedML 28 48 0 24 Jun 2021
Differentially Private Query Release Through Adaptive Projection Sergul Aydore William Brown Michael Kearns K. Kenthapadi Luca Melis Aaron Roth Ankit Siva 43 64 0 11 Mar 2021
A Members First Approach to Enabling LinkedIn's Labor Market Insights at Scale Ryan M. Rogers Adrian Rivera Cardoso Koray Mancuhan Akash Kaura Nikhil T. Gahlawat Neha Jain Paul Ko P. Ahammad 21 11 0 27 Oct 2020
LinkedIn's Audience Engagements API: A Privacy Preserving Data Analytics System at Scale Ryan M. Rogers S. Subramaniam Sean Peng D. Durfee Seunghyun Lee Santosh Kumar Kancha Shraddha Sahay P. Ahammad 27 77 0 14 Feb 2020
SoK: Differential Privacies Damien Desfontaines Balázs Pejó 33 122 0 04 Jun 2019