Differentially Private Covariance Revisited

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Differentially Private Covariance Revisited

28 May 2022

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Papers citing "Differentially Private Covariance Revisited"

17 / 17 papers shown

Title
Private Query Release via the Johnson-Lindenstrauss Transform Aleksandar Nikolov 80 14 0 15 Aug 2022
New Lower Bounds for Private Estimation and a Generalized Fingerprinting Lemma Gautam Kamath Argyris Mouzakis Vikrant Singhal FedML 75 29 0 17 May 2022
Private Robust Estimation by Stabilizing Convex Relaxations Pravesh Kothari Pasin Manurangsi A. Velingker 60 47 0 07 Dec 2021
Private and polynomial time algorithms for learning Gaussians and beyond H. Ashtiani Christopher Liaw 108 48 0 22 Nov 2021
Differential privacy and robust statistics in high dimensions Xiyang Liu Weihao Kong Sewoong Oh 40 69 0 12 Nov 2021
A Private and Computationally-Efficient Estimator for Unbounded Gaussians Gautam Kamath Argyris Mouzakis Vikrant Singhal Thomas Steinke Jonathan R. Ullman 86 40 0 08 Nov 2021
Universal Private Estimators Wei Dong K. Yi 58 20 0 04 Nov 2021
Instance-optimal Mean Estimation Under Differential Privacy Ziyue Huang Yuting Liang K. Yi 57 57 0 01 Jun 2021
Privately Learning Subspaces Vikrant Singhal Thomas Steinke 61 20 0 28 May 2021
On the Sample Complexity of Privately Learning Unbounded High-Dimensional Gaussians Ishaq Aden-Ali H. Ashtiani Gautam Kamath 116 43 0 19 Oct 2020
CoinPress: Practical Private Mean and Covariance Estimation Sourav Biswas Yihe Dong Gautam Kamath Jonathan R. Ullman 69 116 0 11 Jun 2020
AdaCliP: Adaptive Clipping for Private SGD Venkatadheeraj Pichapati A. Suresh Felix X. Yu Sashank J. Reddi Sanjiv Kumar 56 125 0 20 Aug 2019
Private Hypothesis Selection Mark Bun Gautam Kamath Thomas Steinke Zhiwei Steven Wu 66 91 0 30 May 2019
Differentially Private Learning with Adaptive Clipping Galen Andrew Om Thakkar H. B. McMahan Swaroop Ramaswamy FedML 84 343 0 09 May 2019
Privately Learning High-Dimensional Distributions Gautam Kamath Jerry Li Vikrant Singhal Jonathan R. Ullman FedML 90 151 0 01 May 2018
Concentrated Differential Privacy: Simplifications, Extensions, and Lower Bounds Mark Bun Thomas Steinke 92 839 0 06 May 2016
Near-Optimal Algorithms for Differentially-Private Principal Components Kamalika Chaudhuri Anand D. Sarwate Kaushik Sinha 99 158 0 12 Jul 2012

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