DP-PCA: Statistically Optimal and Differentially Private PCA

27 May 2022

Papers citing "DP-PCA: Statistically Optimal and Differentially Private PCA"

34 / 34 papers shown

Title
(Nearly) Optimal Private Linear Regression via Adaptive Clipping Prateeksha Varshney Abhradeep Thakurta Prateek Jain 56 8 0 11 Jul 2022
New Lower Bounds for Private Estimation and a Generalized Fingerprinting Lemma Gautam Kamath Argyris Mouzakis Vikrant Singhal FedML 61 26 0 17 May 2022
On robustness and local differential privacy Mengchu Li Thomas B. Berrett Yi Yu 44 26 0 03 Jan 2022
Private Robust Estimation by Stabilizing Convex Relaxations Pravesh Kothari Pasin Manurangsi A. Velingker 52 47 0 07 Dec 2021
A Private and Computationally-Efficient Estimator for Unbounded Gaussians Gautam Kamath Argyris Mouzakis Vikrant Singhal Thomas Steinke Jonathan R. Ullman 69 40 0 08 Nov 2021
Universal Private Estimators Wei Dong K. Yi 44 20 0 04 Nov 2021
Unbiased Statistical Estimation and Valid Confidence Intervals Under Differential Privacy Christian Covington Xi He James Honaker Gautam Kamath 61 26 0 27 Oct 2021
Tight and Robust Private Mean Estimation with Few Users Cheng-Han Chiang Vahab Mirrokni Hung-yi Lee FedML 53 29 0 22 Oct 2021
High Dimensional Differentially Private Stochastic Optimization with Heavy-tailed Data Lijie Hu Shuo Ni Hanshen Xiao Di Wang 75 53 0 23 Jul 2021
Covariance-Aware Private Mean Estimation Without Private Covariance Estimation Gavin Brown Marco Gaboardi Adam D. Smith Jonathan R. Ullman Lydia Zakynthinou FedML 56 49 0 24 Jun 2021
Robust and Differentially Private Mean Estimation Xiyang Liu Weihao Kong Sham Kakade Sewoong Oh OOD FedML 68 76 0 18 Feb 2021
Streaming k-PCA: Efficient guarantees for Oja's algorithm, beyond rank-one updates De Huang Jonathan Niles-Weed Rachel A. Ward 31 20 0 06 Feb 2021
Hiding Among the Clones: A Simple and Nearly Optimal Analysis of Privacy Amplification by Shuffling Vitaly Feldman Audra McMillan Kunal Talwar FedML 61 161 0 23 Dec 2020
Optimal Private Median Estimation under Minimal Distributional Assumptions Christos Tzamos Emmanouil-Vasileios Vlatakis-Gkaragkounis Ilias Zadik 53 22 0 12 Nov 2020
CoinPress: Practical Private Mean and Covariance Estimation Sourav Biswas Yihe Dong Gautam Kamath Jonathan R. Ullman 55 116 0 11 Jun 2020
Differentially Private Assouad, Fano, and Le Cam Jayadev Acharya Ziteng Sun Huanyu Zhang FedML 52 58 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 Stochastic Convex Optimization with Optimal Rates Raef Bassily Vitaly Feldman Kunal Talwar Abhradeep Thakurta 65 241 0 27 Aug 2019
Average-Case Averages: Private Algorithms for Smooth Sensitivity and Mean Estimation Mark Bun Thomas Steinke 63 76 0 06 Jun 2019
The Cost of Privacy: Optimal Rates of Convergence for Parameter Estimation with Differential Privacy T. Tony Cai Yichen Wang Linjun Zhang 63 168 0 12 Feb 2019
Amplification by Shuffling: From Local to Central Differential Privacy via Anonymity Ulfar Erlingsson Vitaly Feldman Ilya Mironov A. Raghunathan Kunal Talwar Abhradeep Thakurta 172 426 0 29 Nov 2018
Locally Private Gaussian Estimation Matthew Joseph Janardhan Kulkarni Jieming Mao Zhiwei Steven Wu FedML 74 38 0 20 Nov 2018
Privately Learning High-Dimensional Distributions Gautam Kamath Jerry Li Vikrant Singhal Jonathan R. Ullman FedML 86 151 0 01 May 2018
Distributed Differentially-Private Algorithms for Matrix and Tensor Factorization H. Imtiaz Anand D. Sarwate OOD 36 29 0 26 Apr 2018
Calibrating Noise to Variance in Adaptive Data Analysis Vitaly Feldman Thomas Steinke 63 49 0 19 Dec 2017
Finite Sample Differentially Private Confidence Intervals Vishesh Karwa Salil P. Vadhan 55 193 0 10 Nov 2017
Deep Learning with Differential Privacy Martín Abadi Andy Chu Ian Goodfellow H. B. McMahan Ilya Mironov Kunal Talwar Li Zhang FedML SyDa 196 6,113 0 01 Jul 2016
Building a RAPPOR with the Unknown: Privacy-Preserving Learning of Associations and Data Dictionaries Giulia Fanti Vasyl Pihur Ulfar Erlingsson 55 299 0 04 Mar 2015
RAPPOR: Randomized Aggregatable Privacy-Preserving Ordinal Response Ulfar Erlingsson Vasyl Pihur Aleksandra Korolova 92 1,990 0 25 Jul 2014
The Optimal Mechanism in Differential Privacy: Multidimensional Setting Quan Geng Pramod Viswanath 114 123 0 02 Dec 2013
The Noisy Power Method: A Meta Algorithm with Applications Moritz Hardt Eric Price 94 204 0 11 Nov 2013
The Composition Theorem for Differential Privacy Peter Kairouz Sewoong Oh Pramod Viswanath 107 681 0 04 Nov 2013
Bayesian Differential Privacy through Posterior Sampling Christos Dimitrakakis B. Nelson and Zuhe Zhang Aikaterini Mitrokotsa Benjamin I. P. Rubinstein 69 118 0 05 Jun 2013
Near-Optimal Algorithms for Differentially-Private Principal Components Kamalika Chaudhuri Anand D. Sarwate Kaushik Sinha 82 157 0 12 Jul 2012