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A Private and Computationally-Efficient Estimator for Unbounded Gaussians

8 November 2021

Papers citing "A Private and Computationally-Efficient Estimator for Unbounded Gaussians"

38 / 38 papers shown

Title
Private Robust Estimation by Stabilizing Convex Relaxations Pravesh Kothari Pasin Manurangsi A. Velingker 66 47 0 07 Dec 2021
Efficient Mean Estimation with Pure Differential Privacy via a Sum-of-Squares Exponential Mechanism Samuel B. Hopkins Gautam Kamath Mahbod Majid FedML 74 62 0 25 Nov 2021
Private and polynomial time algorithms for learning Gaussians and beyond H. Ashtiani Christopher Liaw 114 48 0 22 Nov 2021
Differential privacy and robust statistics in high dimensions Xiyang Liu Weihao Kong Sewoong Oh 50 69 0 12 Nov 2021
FriendlyCore: Practical Differentially Private Aggregation Eliad Tsfadia E. Cohen Haim Kaplan Yishay Mansour Uri Stemmer 92 36 0 19 Oct 2021
Covariance-Aware Private Mean Estimation Without Private Covariance Estimation Gavin Brown Marco Gaboardi Adam D. Smith Jonathan R. Ullman Lydia Zakynthinou FedML 84 50 0 24 Jun 2021
Privately Learning Mixtures of Axis-Aligned Gaussians Ishaq Aden-Ali H. Ashtiani Christopher Liaw FedML 71 12 0 03 Jun 2021
Instance-optimal Mean Estimation Under Differential Privacy Ziyue Huang Yuting Liang K. Yi 59 57 0 01 Jun 2021
Privately Learning Subspaces Vikrant Singhal Thomas Steinke 68 20 0 28 May 2021
Learning with User-Level Privacy Daniel Levy Ziteng Sun Kareem Amin Satyen Kale Alex Kulesza M. Mohri A. Suresh FedML 88 91 0 23 Feb 2021
Robust and Differentially Private Mean Estimation Xiyang Liu Weihao Kong Sham Kakade Sewoong Oh OOD FedML 84 77 0 18 Feb 2021
Optimal Private Median Estimation under Minimal Distributional Assumptions Christos Tzamos Emmanouil-Vasileios Vlatakis-Gkaragkounis Ilias Zadik 69 22 0 12 Nov 2020
On Differentially Private Stochastic Convex Optimization with Heavy-tailed Data Di Wang Hanshen Xiao S. Devadas Jinhui Xu 71 57 0 21 Oct 2020
On the Sample Complexity of Privately Learning Unbounded High-Dimensional Gaussians Ishaq Aden-Ali H. Ashtiani Gautam Kamath 118 44 0 19 Oct 2020
Learning discrete distributions: user vs item-level privacy Yuhan Liu A. Suresh Felix X. Yu Sanjiv Kumar Michael Riley FedML 113 54 0 27 Jul 2020
CoinPress: Practical Private Mean and Covariance Estimation Sourav Biswas Yihe Dong Gautam Kamath Jonathan R. Ullman 81 117 0 11 Jun 2020
A Primer on Private Statistics Gautam Kamath Jonathan R. Ullman 101 48 0 30 Apr 2020
Differentially Private Assouad, Fano, and Le Cam Jayadev Acharya Ziteng Sun Huanyu Zhang FedML 73 60 0 14 Apr 2020
Privately Learning Markov Random Fields Huanyu Zhang Gautam Kamath Janardhan Kulkarni Zhiwei Steven Wu 72 25 0 21 Feb 2020
Private Mean Estimation of Heavy-Tailed Distributions Gautam Kamath Vikrant Singhal Jonathan R. Ullman 87 99 0 21 Feb 2020
Differentially Private Confidence Intervals Wenxin Du C. Foot Monica Moniot Andrew Bray Adam Groce 67 46 0 07 Jan 2020
Differentially Private Algorithms for Learning Mixtures of Separated Gaussians Gautam Kamath Or Sheffet Vikrant Singhal Jonathan R. Ullman FedML 76 48 0 09 Sep 2019
Differentially private sub-Gaussian location estimators Marco Avella-Medina Victor-Emmanuel Brunel 47 18 0 27 Jun 2019
Average-Case Averages: Private Algorithms for Smooth Sensitivity and Mean Estimation Mark Bun Thomas Steinke 75 76 0 06 Jun 2019
Private Hypothesis Selection Mark Bun Gautam Kamath Thomas Steinke Zhiwei Steven Wu 79 91 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 109 169 0 12 Feb 2019
The Power of The Hybrid Model for Mean Estimation Brendan Avent Yatharth Dubey Aleksandra Korolova 77 17 0 29 Nov 2018
Privately Learning High-Dimensional Distributions Gautam Kamath Jerry Li Vikrant Singhal Jonathan R. Ullman FedML 102 151 0 01 May 2018
Finite Sample Differentially Private Confidence Intervals Vishesh Karwa Salil P. Vadhan 66 195 0 10 Nov 2017
Tight Lower Bounds for Differentially Private Selection Thomas Steinke Jonathan R. Ullman 112 75 0 10 Apr 2017
Concentrated Differential Privacy: Simplifications, Extensions, and Lower Bounds Mark Bun Thomas Steinke 97 840 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 75 513 0 21 Apr 2016
Locating a Small Cluster Privately Kobbi Nissim Uri Stemmer Salil P. Vadhan 53 54 0 19 Apr 2016
Make Up Your Mind: The Price of Online Queries in Differential Privacy Mark Bun Thomas Steinke Jonathan R. Ullman 72 58 0 15 Apr 2016
Between Pure and Approximate Differential Privacy Thomas Steinke Jonathan R. Ullman FedML 112 162 0 24 Jan 2015
Privacy and Statistical Risk: Formalisms and Minimax Bounds Rina Foygel Barber John C. Duchi PILM 74 92 0 15 Dec 2014
Fingerprinting Codes and the Price of Approximate Differential Privacy Mark Bun Jonathan R. Ullman Salil P. Vadhan FedML 105 212 0 13 Nov 2013
A statistical framework for differential privacy Larry A. Wasserman Shuheng Zhou 138 488 0 16 Nov 2008