Tight and Robust Private Mean Estimation with Few Users

Tight and Robust Private Mean Estimation with Few Users

22 October 2021

Cheng-Han Chiang

Vahab Mirrokni

Papers citing "Tight and Robust Private Mean Estimation with Few Users"

17 / 17 papers shown

Title
Efficient Mean Estimation with Pure Differential Privacy via a Sum-of-Squares Exponential Mechanism Samuel B. Hopkins Gautam Kamath Mahbod Majid FedML 47 61 0 25 Nov 2021
FriendlyCore: Practical Differentially Private Aggregation Eliad Tsfadia E. Cohen Haim Kaplan Yishay Mansour Uri Stemmer 35 35 0 19 Oct 2021
Instance-optimal Mean Estimation Under Differential Privacy Ziyue Huang Yuting Liang K. Yi 41 57 0 01 Jun 2021
Learning with User-Level Privacy Daniel Levy Ziteng Sun Kareem Amin Satyen Kale Alex Kulesza M. Mohri A. Suresh FedML 46 90 0 23 Feb 2021
Robust and Differentially Private Mean Estimation Xiyang Liu Weihao Kong Sham Kakade Sewoong Oh OOD FedML 66 77 0 18 Feb 2021
Differentially Private Clustering: Tight Approximation Ratios Badih Ghazi Ravi Kumar Pasin Manurangsi 47 53 0 18 Aug 2020
Learning discrete distributions: user vs item-level privacy Yuhan Liu A. Suresh Felix X. Yu Sanjiv Kumar Michael Riley FedML 69 53 0 27 Jul 2020
Generative Models for Effective ML on Private, Decentralized Datasets S. Augenstein H. B. McMahan Daniel Ramage Swaroop Indra Ramaswamy Peter Kairouz Mingqing Chen Rajiv Mathews Blaise Agüera y Arcas SyDa 85 182 0 15 Nov 2019
Differentially Private SQL with Bounded User Contribution Royce J. Wilson Celia Yuxin Zhang William K. C. Lam Damien Desfontaines Daniel Simmons-Marengo Bryant Gipson 62 149 0 04 Sep 2019
Locally Private k-Means Clustering Uri Stemmer FedML 71 56 0 04 Jul 2019
Estimate Sequences for Stochastic Composite Optimization: Variance Reduction, Acceleration, and Robustness to Noise A. Kulunchakov Julien Mairal 61 45 0 25 Jan 2019
A General Approach to Adding Differential Privacy to Iterative Training Procedures H. B. McMahan Galen Andrew Ulfar Erlingsson Steve Chien Ilya Mironov Nicolas Papernot Peter Kairouz 64 193 0 15 Dec 2018
Privately Learning High-Dimensional Distributions Gautam Kamath Jerry Li Vikrant Singhal Jonathan R. Ullman FedML 83 151 0 01 May 2018
Stochastic model-based minimization of weakly convex functions Damek Davis Dmitriy Drusvyatskiy 72 376 0 17 Mar 2018
Deep Learning with Differential Privacy Martín Abadi Andy Chu Ian Goodfellow H. B. McMahan Ilya Mironov Kunal Talwar Li Zhang FedML SyDa 189 6,109 0 01 Jul 2016
Interactive Fingerprinting Codes and the Hardness of Preventing False Discovery Thomas Steinke Jonathan R. Ullman 76 108 0 05 Oct 2014
A statistical framework for differential privacy Larry A. Wasserman Shuheng Zhou 100 485 0 16 Nov 2008