Optimal rates of convergence for covariance matrix estimation

19 October 2010

Papers citing "Optimal rates of convergence for covariance matrix estimation"

50 / 69 papers shown

Title
High-dimensional Clustering and Signal Recovery under Block Signals Wu Su Yumou Qiu 22 0 0 11 Apr 2025
Optimal Estimation of Structured Covariance Operators Omar Al Ghattas Jiaheng Chen D. Sanz-Alonso Nathan Waniorek 21 3 0 04 Aug 2024
Growing Tiny Networks: Spotting Expressivity Bottlenecks and Fixing Them Optimally Manon Verbockhaven Sylvain Chevallier Guillaume Charpiat 25 4 0 30 May 2024
Distributed High-Dimensional Quantile Regression: Estimation Efficiency and Support Recovery Caixing Wang Ziliang Shen 19 0 0 13 May 2024
Hoeffding's inequality for continuous-time Markov chains Jinpeng Liu Yuanyuan Liu Lin Zhou 13 0 0 23 Apr 2024
High-Dimensional Statistics Philippe Rigollet Jan-Christian Hütter 6 0 0 30 Oct 2023
Sharper dimension-free bounds on the Frobenius distance between sample covariance and its expectation Nikita Puchkin Fedor Noskov V. Spokoiny OT 14 6 0 28 Aug 2023
Learning Networks from Gaussian Graphical Models and Gaussian Free Fields Subhro Ghosh Soumendu Sundar Mukherjee Hoang-Son Tran Ujan Gangopadhyay 17 0 0 04 Aug 2023
Tuning-free one-bit covariance estimation using data-driven dithering S. Dirksen J. Maly 18 7 0 24 Jul 2023
Quantizing Heavy-tailed Data in Statistical Estimation: (Near) Minimax Rates, Covariate Quantization, and Uniform Recovery Junren Chen Michael Kwok-Po Ng Di Wang MQ 13 12 0 30 Dec 2022
Projection inference for high-dimensional covariance matrices with structured shrinkage targets Fabian Mies A. Steland 16 2 0 04 Nov 2022
Dimension-free Bounds for Sum of Dependent Matrices and Operators with Heavy-Tailed Distribution Shogo H. Nakakita Pierre Alquier Masaaki Imaizumi 16 2 0 18 Oct 2022
Distributed Estimation and Inference for Semi-parametric Binary Response Models X. Chen Wenbo Jing Weidong Liu Yichen Zhang 13 2 0 15 Oct 2022
Improved Rates of Bootstrap Approximation for the Operator Norm: A Coordinate-Free Approach Miles E. Lopes 4 3 0 05 Aug 2022
Noise Covariance Estimation in Multi-Task High-dimensional Linear Models Kai Tan Gabriel Romon Pierre C. Bellec 11 4 0 15 Jun 2022
Covariance Estimation: Optimal Dimension-free Guarantees for Adversarial Corruption and Heavy Tails Pedro Abdalla Nikita Zhivotovskiy 17 25 0 17 May 2022
A zero-estimator approach for estimating the signal level in a high-dimensional model-free setting Ilan Livne David Azriel Y. Goldberg 9 0 0 11 May 2022
An efficient GPU-Parallel Coordinate Descent Algorithm for Sparse Precision Matrix Estimation via Scaled Lasso Seunghwan Lee Sang Cheol Kim Donghyeon Yu 7 0 0 28 Mar 2022
ISDE : Independence Structure Density Estimation L. Pujol 17 1 0 18 Mar 2022
Dimensionality Reduction and Wasserstein Stability for Kernel Regression Stephan Eckstein Armin Iske Mathias Trabs 6 4 0 17 Mar 2022
Side Effects of Learning from Low-dimensional Data Embedded in a Euclidean Space Juncai He R. Tsai Rachel A. Ward 28 8 0 01 Mar 2022
High Dimensional Statistical Estimation under Uniformly Dithered One-bit Quantization Junren Chen Cheng-Long Wang Michael Kwok-Po Ng Di Wang MQ 19 17 0 26 Feb 2022
Unlabeled Data Help: Minimax Analysis and Adversarial Robustness Yue Xing Qifan Song Guang Cheng 14 4 0 14 Feb 2022
Optimal Variable Clustering for High-Dimensional Matrix Valued Data Inbeom Lee Siyi Deng Y. Ning 14 1 0 24 Dec 2021
Coherence of high-dimensional random matrices in a Gaussian case : application of the Chen-Stein method M. Boucher D. Chauveau M. Zani 6 0 0 13 Oct 2021
Affine-Invariant Integrated Rank-Weighted Depth: Definition, Properties and Finite Sample Analysis Guillaume Staerman Pavlo Mozharovskyi Stéphan Clémençon 11 10 0 21 Jun 2021
Self-Supervised Metric Learning in Multi-View Data: A Downstream Task Perspective Shulei Wang SSL 17 3 0 14 Jun 2021
New challenges in covariance estimation: multiple structures and coarse quantization J. Maly Tianyu Yang S. Dirksen Holger Rauhut Giuseppe Caire 8 3 0 11 Jun 2021
Covariance estimation under one-bit quantization S. Dirksen J. Maly Holger Rauhut MQ 11 20 0 02 Apr 2021
Estimation of Conditional Mean Operator under the Bandable Covariance Structure Kwangmin Lee Kyoungjae Lee Jaeyong Lee 11 2 0 11 Mar 2021
Robust W-GAN-Based Estimation Under Wasserstein Contamination Zheng Liu Po-Ling Loh 11 5 0 20 Jan 2021
Adversarially Robust Estimate and Risk Analysis in Linear Regression Yue Xing Ruizhi Zhang Guang Cheng AAML 12 26 0 18 Dec 2020
Limiting laws and consistent estimation criteria for fixed and diverging number of spiked eigenvalues Jian-bo Hu Jingfei Zhang Jianhua Guo Ji Zhu 21 1 0 15 Dec 2020
Post-Processed Posteriors for Banded Covariances Kwangmin Lee Kyoungjae Lee Jaeyong Lee 18 5 0 25 Nov 2020
On the Non-Asymptotic Concentration of Heteroskedastic Wishart-type Matrix T. Tony Cai Rungang Han Anru R. Zhang 34 15 0 28 Aug 2020
Robust Gaussian Covariance Estimation in Nearly-Matrix Multiplication Time J. Li Guanghao Ye 8 12 0 23 Jun 2020
$Bootstrapping $\ell_p$-Statistics in High Dimensions$ Bootstrapping $\ell_p$ -Statistics in High Dimensions Alexander Giessing Jianqing Fan 12 4 0 23 Jun 2020
Covariance Estimation for Matrix-valued Data Yichi Zhang Weining Shen Dehan Kong 8 11 0 11 Apr 2020
A Rigorous Theory of Conditional Mean Embeddings I. Klebanov Ingmar Schuster T. Sullivan 14 39 0 02 Dec 2019
Error bound of critical points and KL property of exponent $1/2$ for squared F-norm regularized factorization Ting Tao S. Pan Shujun Bi 8 4 0 11 Nov 2019
Matrix Means and a Novel High-Dimensional Shrinkage Phenomenon A. Lodhia Keith D. Levin Elizaveta Levina 16 3 0 16 Oct 2019
Bootstrapping the Operator Norm in High Dimensions: Error Estimation for Covariance Matrices and Sketching Miles E. Lopes N. Benjamin Erichson Michael W. Mahoney 11 13 0 13 Sep 2019
Optimal estimation of functionals of high-dimensional mean and covariance matrix Jianqing Fan Haolei Weng Yifeng Zhou 19 7 0 20 Aug 2019
Method of Contraction-Expansion (MOCE) for Simultaneous Inference in Linear Models Fei-Yue Wang Ling Zhou Lu Tang P. Song 16 4 0 04 Aug 2019
Faster Algorithms for High-Dimensional Robust Covariance Estimation Yu Cheng Ilias Diakonikolas Rong Ge David P. Woodruff 11 65 0 11 Jun 2019
Integrated conditional moment test and beyond: when the number of covariates is divergent Falong Tan Lixing Zhu 11 7 0 20 May 2019
LR-GLM: High-Dimensional Bayesian Inference Using Low-Rank Data Approximations Brian L. Trippe Jonathan H. Huggins Raj Agrawal Tamara Broderick BDL 12 9 0 17 May 2019
General framework for projection structures E. Belitser N. Nurushev 23 1 0 31 Mar 2019
Affine Invariant Covariance Estimation for Heavy-Tailed Distributions Dmitrii Ostrovskii Alessandro Rudi 19 10 0 08 Feb 2019
Central limit theorem for linear spectral statistics of general separable sample covariance matrices with applications Huiqin Li Yanqing Yin Shu-rong Zheng 15 4 0 23 Jan 2019