The Price of Selection in Differential Privacy

9 February 2017

Papers citing "The Price of Selection in Differential Privacy"

21 / 21 papers shown

Title
Score Attack: A Lower Bound Technique for Optimal Differentially Private Learning T. Tony Cai Yichen Wang Linjun Zhang 46 16 0 13 Mar 2023
Private (Stochastic) Non-Convex Optimization Revisited: Second-Order Stationary Points and Excess Risks Arun Ganesh Daogao Liu Sewoong Oh Abhradeep Thakurta ODL 34 13 0 20 Feb 2023
Tight Data Access Bounds for Private Top- $k$ Selection Hao Wu O. Ohrimenko Anthony Wirth 24 0 0 31 Jan 2023
Majority Vote for Distributed Differentially Private Sign Selection Weidong Liu Jiyuan Tu Xiaojun Mao Xinyu Chen FedML 29 1 0 08 Sep 2022
A Joint Exponential Mechanism For Differentially Private Top- $k$ Jennifer Gillenwater Matthew Joseph Andrés Munoz Medina Mónica Ribero 113 14 0 28 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
Oneshot Differentially Private Top-k Selection Gang Qiao Weijie J. Su Li Zhang 18 31 0 18 May 2021
High-Dimensional Differentially-Private EM Algorithm: Methods and Near-Optimal Statistical Guarantees Zhe Zhang Linjun Zhang FedML 50 3 0 01 Apr 2021
Phase transitions for support recovery under local differential privacy C. Butucea A. Dubois Adrien Saumard FedML 35 3 0 30 Nov 2020
The Cost of Privacy in Generalized Linear Models: Algorithms and Minimax Lower Bounds T. Tony Cai Yichen Wang Linjun Zhang FedML 43 20 0 08 Nov 2020
Permute-and-Flip: A new mechanism for differentially private selection Ryan McKenna Daniel Sheldon 112 47 0 23 Oct 2020
Differentially Private Clustering: Tight Approximation Ratios Badih Ghazi Ravi Kumar Pasin Manurangsi 8 50 0 18 Aug 2020
The power of synergy in differential privacy: Combining a small curator with local randomizers A. Beimel Aleksandra Korolova Kobbi Nissim Or Sheffet Uri Stemmer 34 14 0 18 Dec 2019
Practical Differentially Private Top- $k$ Selection with Pay-what-you-get Composition D. Durfee Ryan M. Rogers 23 82 0 10 May 2019
The Cost of Privacy: Optimal Rates of Convergence for Parameter Estimation with Differential Privacy T. Tony Cai Yichen Wang Linjun Zhang 46 163 0 12 Feb 2019
Distributed Differential Privacy via Shuffling Albert Cheu Adam D. Smith Jonathan R. Ullman David Zeber M. Zhilyaev FedML 51 347 0 04 Aug 2018
Privately Learning High-Dimensional Distributions Gautam Kamath Jerry Li Vikrant Singhal Jonathan R. Ullman FedML 72 149 0 01 May 2018
Scalable Private Learning with PATE Nicolas Papernot Shuang Song Ilya Mironov A. Raghunathan Kunal Talwar Ulfar Erlingsson 41 607 0 24 Feb 2018
Tight Lower Bounds for Locally Differentially Private Selection Jonathan R. Ullman 30 33 0 07 Feb 2018
Tight Lower Bounds for Differentially Private Selection Thomas Steinke Jonathan R. Ullman 21 73 0 10 Apr 2017
The Power of Linear Reconstruction Attacks S. Kasiviswanathan M. Rudelson Adam D. Smith AAML 62 54 0 08 Oct 2012