Covariance regularization by thresholding

20 January 2009

Elizaveta Levina

Papers citing "Covariance regularization by thresholding"

50 / 113 papers shown

Title
Generalized Principal Component Analysis for Large-dimensional Matrix Factor Model Yong He Yujie Hou Haixia Liu Yalin Wang 31 0 0 10 Nov 2024
Sparse Covariance Neural Networks Andrea Cavallo Zhan Gao Elvin Isufi 33 1 0 02 Oct 2024
TAVRNN: Temporal Attention-enhanced Variational Graph RNN Captures Neural Dynamics and Behavior M. Khajehnejad Forough Habibollahi Ahmad Khajehnejad Brett J. Kagan Adeel Razi 23 1 0 01 Oct 2024
Scalable and non-iterative graphical model estimation Kshitij Khare S. Rahman B. Rajaratnam Jiayuan Zhou 19 0 0 21 Aug 2024
DC Algorithm for Estimation of Sparse Gaussian Graphical Models Tomokaze Shiratori Yuichi Takano 28 0 0 08 Aug 2024
Optimal Estimation of Structured Covariance Operators Omar Al Ghattas Jiaheng Chen D. Sanz-Alonso Nathan Waniorek 39 3 0 04 Aug 2024
High-dimensional Covariance Estimation by Pairwise Likelihood Truncation Alessandro Casa Davide Ferrari Zhendong Huang 16 1 0 10 Jul 2024
Covariance Operator Estimation via Adaptive Thresholding Omar Al Ghattas D. Sanz-Alonso 38 1 0 28 May 2024
Power-Enhanced Two-Sample Mean Tests for High-Dimensional Compositional Data with Application to Microbiome Data Analysis Danning Li Lingzhou Xue Haoyi Yang Xiufan Yu 34 4 0 04 May 2024
Dimension-free Structured Covariance Estimation Nikita Puchkin Maxim Rakhuba 17 1 0 15 Feb 2024
Regression graphs and sparsity-inducing reparametrizations Jakub Rybák Heather Battey Karthik Bharath 15 0 0 14 Feb 2024
Efficient Computation of Sparse and Robust Maximum Association Estimators Pia Pfeiffer Andreas Alfons P. Filzmoser 17 0 0 29 Nov 2023
Covariance Operator Estimation: Sparsity, Lengthscale, and Ensemble Kalman Filters Omar Al Ghattas Jiaheng Chen D. Sanz-Alonso Nathan Waniorek 21 4 0 25 Oct 2023
Statistical inference of high-dimensional vector autoregressive time series with non-i.i.d. innovations Yunyi Zhang 18 1 0 11 Oct 2023
Sharper dimension-free bounds on the Frobenius distance between sample covariance and its expectation Nikita Puchkin Fedor Noskov V. Spokoiny OT 29 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 22 0 0 04 Aug 2023
Tuning-free one-bit covariance estimation using data-driven dithering S. Dirksen J. Maly 23 7 0 24 Jul 2023
Statistical analysis for a penalized EM algorithm in high-dimensional mixture linear regression model Ning Wang Xin Zhang Qing Mai 13 1 0 21 Jul 2023
On Sufficient Graphical Models Bing Li Kyongwon Kim 17 0 0 10 Jul 2023
Scattering Spectra Models for Physics S. Cheng Rudy Morel Erwan Allys Brice Ménard S. Mallat 19 8 0 29 Jun 2023
Distributed Semi-Supervised Sparse Statistical Inference Jiyuan Tu Weidong Liu Xiaojun Mao Mingyue Xu 21 1 0 17 Jun 2023
Online Detection of Changes in Moment-Based Projections: When to Retrain Deep Learners or Update Portfolios? A. Steland 26 0 0 14 Feb 2023
Dimension Reduction and MARS Yu Liu Degui Li Yingcun Xia 6 1 0 11 Feb 2023
Statistical Inference for Ultrahigh Dimensional Location Parameter Based on Spatial Median Guanghui Cheng Liuhua Peng Changliang Zou 21 5 0 09 Jan 2023
On High dimensional Poisson models with measurement error: hypothesis testing for nonlinear nonconvex optimization Fei Jiang Yeqing Zhou Jianxuan Liu Yanyuan Ma 16 1 0 31 Dec 2022
Quantizing Heavy-tailed Data in Statistical Estimation: (Near) Minimax Rates, Covariate Quantization, and Uniform Recovery Junren Chen Michael Kwok-Po Ng Di Wang MQ 28 12 0 30 Dec 2022
Clustering through Feature Space Sequence Discovery and Analysis Guobin Shi 9 0 0 02 Dec 2022
Projection inference for high-dimensional covariance matrices with structured shrinkage targets Fabian Mies A. Steland 24 2 0 04 Nov 2022
Inferring independent sets of Gaussian variables after thresholding correlations Arkajyoti Saha Daniela Witten Jacob Bien 19 3 0 02 Nov 2022
The Generalized Elastic Net for least squares regression with network-aligned signal and correlated design Huy Tran Sansen Wei Claire Donnat 10 2 0 01 Nov 2022
Bregman Divergence-Based Data Integration with Application to Polygenic Risk Score (PRS) Heterogeneity Adjustment Qinmengge Li M. Patrick Haihan Zhang Chachrit Khunsriraksakul P. Stuart ... James T. Elder Dajiang J. Liu Jian Kang L. Tsoi Kevin He 37 0 0 12 Oct 2022
Automatic sparse PCA for high-dimensional data K. Yata M. Aoshima 14 1 0 29 Sep 2022
Optimal Sparse Estimation of High Dimensional Heavy-tailed Time Series Sagnik Halder George Michailidis AI4TS 10 0 0 19 Sep 2022
Sparse Hanson-Wright Inequality for a Bilinear Form of Sub-Gaussian Variables Seongoh Park Xinlei Wang Johan Lim 9 4 0 13 Sep 2022
Large covariance matrix estimation via penalized log-det heuristics E. Bernardi M. Farné 23 0 0 11 Sep 2022
Majority Vote for Distributed Differentially Private Sign Selection Weidong Liu Jiyuan Tu Xiaojun Mao Xinyu Chen FedML 29 1 0 08 Sep 2022
Non-Asymptotic Analysis of Ensemble Kalman Updates: Effective Dimension and Localization Omar Al Ghattas D. Sanz-Alonso 30 13 0 05 Aug 2022
Adaptive Functional Thresholding for Sparse Covariance Function Estimation in High Dimensions Qin Fang Shaojun Guo Xinghao Qiao 14 6 0 14 Jul 2022
Tyler's and Maronna's M-estimators: Non-Asymptotic Concentration Results Elad Romanov Gil Kur B. Nadler 13 3 0 21 Jun 2022
Noise Covariance Estimation in Multi-Task High-dimensional Linear Models Kai Tan Gabriel Romon Pierre C. Bellec 19 4 0 15 Jun 2022
Covariance Estimation: Optimal Dimension-free Guarantees for Adversarial Corruption and Heavy Tails Pedro Abdalla Nikita Zhivotovskiy 32 25 0 17 May 2022
An Equivalence Principle for the Spectrum of Random Inner-Product Kernel Matrices with Polynomial Scalings Yue M. Lu H. Yau 24 24 0 12 May 2022
Selective inference for k-means clustering Yiqun T. Chen Daniela Witten 25 43 0 29 Mar 2022
An efficient GPU-Parallel Coordinate Descent Algorithm for Sparse Precision Matrix Estimation via Scaled Lasso Seunghwan Lee Sang Cheol Kim Donghyeon Yu 9 0 0 28 Mar 2022
Bayesian Nonlinear Models for Repeated Measurement Data: An Overview, Implementation, and Applications Se Yoon Lee 19 18 0 28 Jan 2022
Modelling matrix time series via a tensor CP-decomposition Jinyuan Chang Jingjing He Lin Yang Q. Yao AI4TS 41 29 0 31 Dec 2021
New Hard-thresholding Rules based on Data Splitting in High-dimensional Imbalanced Classification Arezou Mojiri Abbas Khalili A. Z. Hamadani 9 0 0 05 Nov 2021
Covariance Structure Estimation with Laplace Approximation Bongjung Sung Jaeyong Lee CML 20 1 0 04 Nov 2021
Classification of high-dimensional data with spiked covariance matrix structure Yin-Jen Chen M. Tang 62 0 0 05 Oct 2021
A Bernstein-type Inequality for High Dimensional Linear Processes with Applications to Robust Estimation of Time Series Regressions Linbo Liu Danna Zhang AI4TS 40 1 0 21 Sep 2021