User-Friendly Covariance Estimation for Heavy-Tailed Distributions

User-Friendly Covariance Estimation for Heavy-Tailed Distributions

5 November 2018

Stanislav Minsker

Papers citing "User-Friendly Covariance Estimation for Heavy-Tailed Distributions"

12 / 12 papers shown

Title
Adaptive posterior distributions for uncertainty analysis of covariance matrices in Bayesian inversion problems for multioutput signals E. Curbelo Luca Martino F. Llorente D. Delgado-Gomez 49 1 0 03 Jan 2025
Tuning-free one-bit covariance estimation using data-driven dithering S. Dirksen J. Maly 23 7 0 24 Jul 2023
Provably Robust Temporal Difference Learning for Heavy-Tailed Rewards Semih Cayci A. Eryilmaz 23 2 0 20 Jun 2023
Robust Functional Data Analysis for Discretely Observed Data Lingxuan Shao Fang Yao 13 0 0 25 May 2023
Covariance Estimation under Missing Observations and $L_4-L_2$ Moment Equivalence Pedro Abdalla 31 1 0 22 May 2023
Statistically Optimal Robust Mean and Covariance Estimation for Anisotropic Gaussians A. Minasyan Nikita Zhivotovskiy 29 9 0 21 Jan 2023
Covariance Estimation: Optimal Dimension-free Guarantees for Adversarial Corruption and Heavy Tails Pedro Abdalla Nikita Zhivotovskiy 38 25 0 17 May 2022
Robust parameter estimation of regression model under weakened moment assumptions Kangqiang Li Songqiao Tang Lixin Zhang 26 0 0 08 Dec 2021
Do we need to estimate the variance in robust mean estimation? Qiang Sun OOD 29 7 0 30 Jun 2021
Covariance estimation under one-bit quantization S. Dirksen J. Maly Holger Rauhut MQ 31 20 0 02 Apr 2021
Rejoinder: On nearly assumption-free tests of nominal confidence interval coverage for causal parameters estimated by machine learning Lin Liu Rajarshi Mukherjee J. M. Robins CML 33 16 0 07 Aug 2020
Model-free Feature Screening and FDR Control with Knockoff Features Wanjun Liu Y. Ke Jingyuan Liu Runze Li 24 57 0 19 Aug 2019