On the Sample Complexity of Privately Learning Unbounded High-Dimensional Gaussians

19 October 2020

Papers citing "On the Sample Complexity of Privately Learning Unbounded High-Dimensional Gaussians"

36 / 36 papers shown

Title
Learning with Differentially Private (Sliced) Wasserstein Gradients David Rodríguez-Vítores Clément Lalanne Jean-Michel Loubes FedML 75 0 0 03 Feb 2025
Learning discrete distributions: user vs item-level privacy Yuhan Liu A. Suresh Felix X. Yu Sanjiv Kumar Michael Riley FedML 62 53 0 27 Jul 2020
CoinPress: Practical Private Mean and Covariance Estimation Sourav Biswas Yihe Dong Gautam Kamath Jonathan R. Ullman 51 116 0 11 Jun 2020
A Primer on Private Statistics Gautam Kamath Jonathan R. Ullman 49 48 0 30 Apr 2020
Differentially Private Assouad, Fano, and Le Cam Jayadev Acharya Ziteng Sun Huanyu Zhang FedML 47 58 0 14 Apr 2020
Locally Private Hypothesis Selection Sivakanth Gopi Gautam Kamath Janardhan Kulkarni Aleksandar Nikolov Zhiwei Steven Wu Huanyu Zhang 43 26 0 21 Feb 2020
Private Mean Estimation of Heavy-Tailed Distributions Gautam Kamath Vikrant Singhal Jonathan R. Ullman 52 99 0 21 Feb 2020
Privately Learning Markov Random Fields Huanyu Zhang Gautam Kamath Janardhan Kulkarni Zhiwei Steven Wu 58 25 0 21 Feb 2020
Differentially Private Confidence Intervals Wenxin Du C. Foot Monica Moniot Andrew Bray Adam Groce 34 46 0 07 Jan 2020
On the Sample Complexity of Learning Sum-Product Networks Ishaq Aden-Ali H. Ashtiani TPM 20 2 0 05 Dec 2019
Differentially Private Algorithms for Learning Mixtures of Separated Gaussians Gautam Kamath Or Sheffet Vikrant Singhal Jonathan R. Ullman FedML 40 48 0 09 Sep 2019
Average-Case Averages: Private Algorithms for Smooth Sensitivity and Mean Estimation Mark Bun Thomas Steinke 59 74 0 06 Jun 2019
Private Hypothesis Selection Mark Bun Gautam Kamath Thomas Steinke Zhiwei Steven Wu 32 90 0 30 May 2019
The Cost of Privacy: Optimal Rates of Convergence for Parameter Estimation with Differential Privacy T. Tony Cai Yichen Wang Linjun Zhang 54 165 0 12 Feb 2019
The Optimal Approximation Factor in Density Estimation Olivier Bousquet D. Kane Shay Moran 49 19 0 10 Feb 2019
The total variation distance between high-dimensional Gaussians with the same mean Luc Devroye Abbas Mehrabian Tommy Reddad 45 225 0 19 Oct 2018
Privately Learning High-Dimensional Distributions Gautam Kamath Jerry Li Vikrant Singhal Jonathan R. Ullman FedML 81 151 0 01 May 2018
Collecting Telemetry Data Privately Bolin Ding Janardhan Kulkarni Sergey Yekhanin 40 676 0 05 Dec 2017
Finite Sample Differentially Private Confidence Intervals Vishesh Karwa Salil P. Vadhan 47 193 0 10 Nov 2017
Sample-Efficient Learning of Mixtures H. Ashtiani Shai Ben-David Abbas Mehrabian 33 25 0 06 Jun 2017
Tight Lower Bounds for Differentially Private Selection Thomas Steinke Jonathan R. Ullman 59 73 0 10 Apr 2017
Membership Inference Attacks against Machine Learning Models Reza Shokri M. Stronati Congzheng Song Vitaly Shmatikov SLR MIALM MIACV 203 4,075 0 18 Oct 2016
Concentrated Differential Privacy: Simplifications, Extensions, and Lower Bounds Mark Bun Thomas Steinke 55 823 0 06 May 2016
Robust Estimators in High Dimensions without the Computational Intractability Ilias Diakonikolas Gautam Kamath D. Kane Jingkai Li Ankur Moitra Alistair Stewart 64 511 0 21 Apr 2016
Locating a Small Cluster Privately Kobbi Nissim Uri Stemmer Salil P. Vadhan 19 53 0 19 Apr 2016
Make Up Your Mind: The Price of Online Queries in Differential Privacy Mark Bun Thomas Steinke Jonathan R. Ullman 49 58 0 15 Apr 2016
Concentrated Differential Privacy Cynthia Dwork G. Rothblum 50 446 0 06 Mar 2016
Between Pure and Approximate Differential Privacy Thomas Steinke Jonathan R. Ullman FedML 55 159 0 24 Jan 2015
Interactive Fingerprinting Codes and the Hardness of Preventing False Discovery Thomas Steinke Jonathan R. Ullman 57 108 0 05 Oct 2014
RAPPOR: Randomized Aggregatable Privacy-Preserving Ordinal Response Ulfar Erlingsson Vasyl Pihur Aleksandra Korolova 59 1,977 0 25 Jul 2014
Near-optimal-sample estimators for spherical Gaussian mixtures A. Suresh Ashkan Jafarpour A. Orlitsky Jayadev Acharya 64 92 0 19 Feb 2014
Faster and Sample Near-Optimal Algorithms for Proper Learning Mixtures of Gaussians C. Daskalakis Gautam Kamath 134 92 0 04 Dec 2013
Fingerprinting Codes and the Price of Approximate Differential Privacy Mark Bun Jonathan R. Ullman Salil P. Vadhan FedML 45 211 0 13 Nov 2013
Learning Poisson Binomial Distributions C. Daskalakis Ilias Diakonikolas Rocco A. Servedio SSL 113 120 0 13 Jul 2011
On the Geometry of Differential Privacy Moritz Hardt Kunal Talwar 92 462 0 21 Jul 2009
Density estimation in linear time Satyaki Mahalanabis Daniel Stefankovic 78 23 0 18 Dec 2007