Privately Learning Smooth Distributions on the Hypercube by Projections

16 September 2024

Papers citing "Privately Learning Smooth Distributions on the Hypercube by Projections"

38 / 38 papers shown

Title
Learning with Differentially Private (Sliced) Wasserstein Gradients David Rodríguez-Vítores Clément Lalanne Jean-Michel Loubes FedML 105 0 0 03 Feb 2025
MCMC for Bayesian nonparametric mixture modeling under differential privacy Mario Beraha Stefano Favaro Vinayak Rao 52 1 0 15 Oct 2023
About the Cost of Central Privacy in Density Estimation Clément Lalanne Aurélien Garivier Rémi Gribonval 50 3 0 26 Jun 2023
A Polynomial Time, Pure Differentially Private Estimator for Binary Product Distributions Vikrant Singhal 73 9 0 13 Apr 2023
Private Statistical Estimation of Many Quantiles Clément Lalanne Aurélien Garivier Rémi Gribonval 49 6 0 14 Feb 2023
On the Statistical Complexity of Estimation and Testing under Privacy Constraints Clément Lalanne Aurélien Garivier Rémi Gribonval 53 7 0 05 Oct 2022
On rate optimal private regression under local differential privacy László Gyorfi Martin Kroll 39 8 0 31 May 2022
Membership Inference Attacks From First Principles Nicholas Carlini Steve Chien Milad Nasr Shuang Song Andreas Terzis Florian Tramèr MIACV MIALM 83 704 0 07 Dec 2021
Multivariate density estimation from privatised data: universal consistency and minimax rates László Gyorfi Martin Kroll 24 4 0 27 Jul 2021
Optimal Rates for Nonparametric Density Estimation under Communication Constraints Jayadev Acharya C. Canonne Aditya Singh Himanshu Tyagi OT 47 12 0 21 Jul 2021
Covariance-Aware Private Mean Estimation Without Private Covariance Estimation Gavin Brown Marco Gaboardi Adam D. Smith Jonathan R. Ullman Lydia Zakynthinou FedML 65 50 0 24 Jun 2021
The Permute-and-Flip Mechanism is Identical to Report-Noisy-Max with Exponential Noise Zeyu Ding Daniel Kifer S. Saghaian Thomas Steinke Yuxin Wang Yingtai Xiao Qiang Yan 47 28 0 15 May 2021
Inference under Information Constraints III: Local Privacy Constraints Jayadev Acharya C. Canonne Cody R. Freitag Ziteng Sun Himanshu Tyagi 65 35 0 20 Jan 2021
Strongly universally consistent nonparametric regression and classification with privatised data Thomas B. Berrett László Gyorfi Harro Walk 35 16 0 31 Oct 2020
Permute-and-Flip: A new mechanism for differentially private selection Ryan McKenna Daniel Sheldon 158 50 0 23 Oct 2020
On the Sample Complexity of Privately Learning Unbounded High-Dimensional Gaussians Ishaq Aden-Ali H. Ashtiani Gautam Kamath 110 43 0 19 Oct 2020
CoinPress: Practical Private Mean and Covariance Estimation Sourav Biswas Yihe Dong Gautam Kamath Jonathan R. Ullman 63 116 0 11 Jun 2020
Differentially Private Assouad, Fano, and Le Cam Jayadev Acharya Ziteng Sun Huanyu Zhang FedML 59 59 0 14 Apr 2020
Private Mean Estimation of Heavy-Tailed Distributions Gautam Kamath Vikrant Singhal Jonathan R. Ullman 78 100 0 21 Feb 2020
Private Hypothesis Selection Mark Bun Gautam Kamath Thomas Steinke Zhiwei Steven Wu 59 91 0 30 May 2019
Local differential privacy: Elbow effect in optimal density estimation and adaptation over Besov ellipsoids C. Butucea A. Dubois Martin Kroll Adrien Saumard 63 44 0 05 Mar 2019
The Cost of Privacy: Optimal Rates of Convergence for Parameter Estimation with Differential Privacy T. Tony Cai Yichen Wang Linjun Zhang 68 168 0 12 Feb 2019
Private Selection from Private Candidates Jingcheng Liu Kunal Talwar 63 132 0 19 Nov 2018
Privately Learning High-Dimensional Distributions Gautam Kamath Jerry Li Vikrant Singhal Jonathan R. Ullman FedML 90 151 0 01 May 2018
Collecting Telemetry Data Privately Bolin Ding Janardhan Kulkarni Sergey Yekhanin 55 686 0 05 Dec 2017
Finite Sample Differentially Private Confidence Intervals Vishesh Karwa Salil P. Vadhan 60 194 0 10 Nov 2017
Concentrated Differential Privacy: Simplifications, Extensions, and Lower Bounds Mark Bun Thomas Steinke 84 835 0 06 May 2016
Minimax Optimal Procedures for Locally Private Estimation John C. Duchi Martin J. Wainwright Michael I. Jordan 73 435 0 08 Apr 2016
Concentrated Differential Privacy Cynthia Dwork G. Rothblum 70 452 0 06 Mar 2016
Privacy and Statistical Risk: Formalisms and Minimax Bounds Rina Foygel Barber John C. Duchi PILM 67 92 0 15 Dec 2014
RAPPOR: Randomized Aggregatable Privacy-Preserving Ordinal Response Ulfar Erlingsson Vasyl Pihur Aleksandra Korolova 96 1,992 0 25 Jul 2014
Adaptive pointwise estimation of conditional density function Karine Bertin C. Lacour Vincent Rivoirard 96 39 0 28 Dec 2013
Local Privacy, Data Processing Inequalities, and Statistical Minimax Rates John C. Duchi Michael I. Jordan Martin J. Wainwright FedML 83 102 0 13 Feb 2013
Adaptive functional linear regression Fabienne Comte Jan Johannes 112 59 0 12 Dec 2011
Bandwidth selection in kernel density estimation: Oracle inequalities and adaptive minimax optimality A. Goldenshluger O. Lepski 379 245 0 06 Sep 2010
A statistical framework for differential privacy Larry A. Wasserman Shuheng Zhou 105 485 0 16 Nov 2008
What Can We Learn Privately? S. Kasiviswanathan Homin K. Lee Kobbi Nissim Sofya Raskhodnikova Adam D. Smith 137 1,466 0 06 Mar 2008
Structural adaptation via $L_p$ -norm oracle inequalities A. Goldenshluger O. Lepski 1.0K 66 0 19 Apr 2007