The Masked Sample Covariance Estimator: An Analysis via Matrix Concentration Inequalities

8 September 2011

Papers citing "The Masked Sample Covariance Estimator: An Analysis via Matrix Concentration Inequalities"

12 / 12 papers shown

Title
Tuning-free one-bit covariance estimation using data-driven dithering S. Dirksen J. Maly 23 7 0 24 Jul 2023
A Fast Algorithm for Adaptive Private Mean Estimation John C. Duchi Saminul Haque Rohith Kuditipudi FedML 27 15 0 17 Jan 2023
Communication-efficient Distributed Newton-like Optimization with Gradients and M-estimators Ziyan Yin 32 0 0 13 Jul 2022
On the fast convergence of minibatch heavy ball momentum Raghu Bollapragada Tyler Chen Rachel A. Ward 32 17 0 15 Jun 2022
U-statistics of growing order and sub-Gaussian mean estimators with sharp constants Stanislav Minsker 21 13 0 24 Feb 2022
Federated Asymptotics: a model to compare federated learning algorithms Gary Cheng Karan N. Chadha John C. Duchi FedML 16 16 0 16 Aug 2021
Covariance estimation under one-bit quantization S. Dirksen J. Maly Holger Rauhut MQ 31 20 0 02 Apr 2021
Distributed estimation of the inverse Hessian by determinantal averaging Michal Derezinski Michael W. Mahoney 25 28 0 28 May 2019
Four lectures on probabilistic methods for data science Roman Vershynin 16 25 0 20 Dec 2016
The Expected Norm of a Sum of Independent Random Matrices: An Elementary Approach J. Tropp 34 55 0 15 Jun 2015
Second-Order Matrix Concentration Inequalities J. Tropp 210 28 0 22 Apr 2015
Divide and Conquer Kernel Ridge Regression: A Distributed Algorithm with Minimax Optimal Rates Yuchen Zhang John C. Duchi Martin J. Wainwright 51 373 0 22 May 2013