A self-calibrated direct approach to precision matrix estimation and linear discriminant analysis in high dimensions

Dynamic linear discriminant analysis in high dimensional space

(2020) Binyan Jiang et al.   BERNOULLI

A Survey of Tuning Parameter Selection for High-Dimensional Regression

(2020) Yunan Wu et al.   Annual Review of Statistics and Its Application

High dimensional linear discriminant analysis: optimality, adaptive algorithm and missing data

(2019) T. Tony Cai et al.   JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY

An efficient ADMM algorithm for high dimensional precision matrix estimation via penalized quadratic loss

(2019) Cheng Wang et al.   COMPUTATIONAL STATISTICS & DATA ANALYSIS

SIS: An R Package for Sure Independence Screening in Ultrahigh-Dimensional Statistical Models

(2018) Diego Franco Saldana et al.   Journal of Statistical Software

Prediction error bounds for linear regression with the TREX

(2018) Jacob Bien et al.   TEST

Prediction error bounds for linear regression with the TREX

(2018) Jacob Bien et al.   TEST

A linear programming model for selection of sparse high-dimensional multiperiod portfolios

(2018) Chi Seng Pun et al.   EUROPEAN JOURNAL OF OPERATIONAL RESEARCH

Big Data Challenges of High-Dimensional Continuous-Time Mean-Variance Portfolio Selection and a Remedy

(2017) Mei Choi Chiu et al.   RISK ANALYSIS

Cellwise robust regularized discriminant analysis

(2017) Stéphanie Aerts et al.   Statistical Analysis and Data Mining

Estimating sparse precision matrix: Optimal rates of convergence and adaptive estimation

(2016) T. Tony Cai et al.   ANNALS OF STATISTICS

Resolution of Degeneracy in Merton's Portfolio Problem

(2016) Chi Seng Pun et al.   SIAM Journal on Financial Mathematics

Sparse precision matrix estimation via lasso penalized D-trace loss

(2014) T. Zhang et al.   BIOMETRIKA

Graphical lasso quadratic discriminant function and its application to character recognition

(2013) Bo Xu et al.   NEUROCOMPUTING

Scaled sparse linear regression

(2012) T. Sun et al.   BIOMETRIKA

A Direct Estimation Approach to Sparse Linear Discriminant Analysis

(2012) Tony Cai et al.   JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION

Tuning parameter selection in high dimensional penalized likelihood

(2012) Yingying Fan et al.   JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY

Gradient methods for minimizing composite functions

(2012) Yu. Nesterov   MATHEMATICAL PROGRAMMING

A Unified Framework for High-Dimensional Analysis of $M$-Estimators with Decomposable Regularizers

(2012) Sahand N. Negahban et al.   STATISTICAL SCIENCE

Sparse linear discriminant analysis by thresholding for high dimensional data

(2011) Jun Shao et al.   ANNALS OF STATISTICS

Square-root lasso: pivotal recovery of sparse signals via conic programming

(2011) A. Belloni et al.   BIOMETRIKA

A Constrainedℓ1Minimization Approach to Sparse Precision Matrix Estimation

(2011) Tony Cai et al.   JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION

High-dimensional covariance estimation by minimizing ℓ1-penalized log-determinant divergence

(2011) Pradeep Ravikumar et al.   Electronic Journal of Statistics

Optimal rates of convergence for covariance matrix estimation

(2010) T. Tony Cai et al.   ANNALS OF STATISTICS

Regularization Parameter Selections via Generalized Information Criterion

(2010) Yiyun Zhang et al.   JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION

ℓ1-penalization for mixture regression models

(2010) Nicolas Städler et al.   TEST

Operator norm consistent estimation of large-dimensional sparse covariance matrices

(2009) Noureddine El Karoui   ANNALS OF STATISTICS

High-dimensional classification using features annealed independence rules

(2009) Jianqing Fan et al.   ANNALS OF STATISTICS

Covariance regularization by thresholding

(2009) Peter J. Bickel et al.   ANNALS OF STATISTICS

A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems

(2009) Amir Beck et al.   SIAM Journal on Imaging Sciences

Regularized estimation of large covariance matrices

(2008) Peter J. Bickel et al.   ANNALS OF STATISTICS

Extended Bayesian information criteria for model selection with large model spaces

(2008) J. Chen et al.   BIOMETRIKA

First-Order Methods for Sparse Covariance Selection

(2008) Alexandre d'Aspremont et al.   SIAM JOURNAL ON MATRIX ANALYSIS AND APPLICATIONS

Sparse permutation invariant covariance estimation

(2008) Adam J. Rothman et al.   Electronic Journal of Statistics