2007 - Fellow of the American Statistical Association (ASA)
His scientific interests lie mostly in Applied mathematics, Estimator, Statistics, Feature selection and Linear regression. He has researched Applied mathematics in several fields, including Tensor product of Hilbert spaces, Minimax and Matrix norm. His Minimax research integrates issues from Mean squared error, Penalty method, Probability distribution and Shrinkage estimator.
His research integrates issues of Joint probability distribution, Norm, Algorithm, Covariance matrix and Uniform boundedness in his study of Estimator. His Feature selection research is multidisciplinary, incorporating perspectives in Regression analysis, Covariate, Approximate solution and Model selection. Cun-Hui Zhang regularly ties together related areas like Lasso in his Linear regression studies.
Cun-Hui Zhang focuses on Estimator, Applied mathematics, Statistics, Combinatorics and Algorithm. His Estimator research is multidisciplinary, relying on both Linear regression, Mathematical optimization, Minimax, Elastic net regularization and Rate of convergence. Cun-Hui Zhang works mostly in the field of Linear regression, limiting it down to topics relating to Lasso and, in certain cases, Feature selection.
His work carried out in the field of Minimax brings together such families of science as Shrinkage estimator, Piecewise and Bayes' theorem. Cun-Hui Zhang studied Applied mathematics and White noise that intersect with Equivalence. His Combinatorics research incorporates elements of Upper and lower bounds, Random variable and Isotonic regression.
Cun-Hui Zhang mainly investigates Estimator, Applied mathematics, Combinatorics, Series and Algorithm. His Estimator research is under the purview of Statistics. The Applied mathematics study combines topics in areas such as Additive model, Sample size determination, Least squares and Penalized likelihood.
He combines subjects such as Lasso, Asymptotic distribution and Isotonic regression with his study of Combinatorics. His Series research also works with subjects such as
Cun-Hui Zhang spends much of his time researching Combinatorics, Estimator, Lasso, Minimax and Algorithm. Cun-Hui Zhang has researched Combinatorics in several fields, including Norm and Asymptotic distribution. His Estimator research is within the category of Statistics.
The various areas that Cun-Hui Zhang examines in his Lasso study include Separable space, Differentiable function, Linear regression and Integrable system. His research investigates the connection between Separable space and topics such as Feature selection that intersect with issues in Consistency. Cun-Hui Zhang combines subjects such as Bayes estimator, Convergence, Shrinkage estimator and Piecewise with his study of Minimax.
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Nearly unbiased variable selection under minimax concave penalty
Cun Hui Zhang.
Annals of Statistics (2010)
Confidence intervals for low dimensional parameters in high dimensional linear models
Cun-Hui Zhang;Stephanie S. Zhang.
Journal of The Royal Statistical Society Series B-statistical Methodology (2014)
The sparsity and bias of the Lasso selection in high-dimensional linear regression
Cun Hui Zhang;Jian Huang.
Annals of Statistics (2008)
Adaptive Lasso for sparse high-dimensional regression models
Jian Huang;Shuangge Ma;Cun Hui Zhang.
Statistica Sinica (2008)
Scaled sparse linear regression
Tingni Sun;Cun Hui Zhang.
The multivariate L1-median and associated data depth
Yehuda Vardi;Cun Hui Zhang.
Proceedings of the National Academy of Sciences of the United States of America (2000)
Optimal rates of convergence for covariance matrix estimation
T. Tony Cai;Cun Hui Zhang;Harrison H. Zhou.
Annals of Statistics (2010)
A group bridge approach for variable selection
Jian Huang;Shuange Ma;Huiliang Xie;Cun Hui Zhang.
A General Theory of Concave Regularization for High-Dimensional Sparse Estimation Problems
Cun-Hui Zhang;Tong Zhang.
Statistical Science (2012)
Fourier Methods for Estimating Mixing Densities and Distributions
Annals of Statistics (1990)
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