D-Index & Metrics Best Publications

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Mathematics D-index 41 Citations 12,588 173 World Ranking 1252 National Ranking 576

Research.com Recognitions

Awards & Achievements

2007 - Fellow of the American Statistical Association (ASA)

Overview

What is he best known for?

The fields of study he is best known for:

  • Statistics
  • Mathematical analysis
  • Normal distribution

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.

His most cited work include:

  • Nearly unbiased variable selection under minimax concave penalty (2149 citations)
  • The sparsity and bias of the Lasso selection in high-dimensional linear regression (580 citations)
  • Confidence intervals for low dimensional parameters in high dimensional linear models (514 citations)

What are the main themes of his work throughout his whole career to date?

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.

He most often published in these fields:

  • Estimator (33.51%)
  • Applied mathematics (31.35%)
  • Statistics (21.62%)

What were the highlights of his more recent work (between 2017-2021)?

  • Estimator (33.51%)
  • Applied mathematics (31.35%)
  • Combinatorics (18.92%)

In recent papers he was focusing on the following fields of study:

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

  • Tensor which intersects with area such as Model selection,
  • Dimensionality reduction and related Orthographic projection,
  • Range that intertwine with fields like Data collection, Computational science and Eigen analysis,
  • Factor analysis that connect with fields like Pattern recognition and Artificial intelligence. His research investigates the link between Algorithm and topics such as High dimensional that cross with problems in Inference.

Between 2017 and 2021, his most popular works were:

  • Group-Linear Empirical Bayes Estimates for a Heteroscedastic Normal Mean (20 citations)
  • Statistical Foundations of Data Science (12 citations)
  • Statistically Optimal and Computationally Efficient Low Rank Tensor Completion from Noisy Entries (10 citations)

In his most recent research, the most cited papers focused on:

  • Statistics
  • Mathematical analysis
  • Normal distribution

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.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Nearly unbiased variable selection under minimax concave penalty

Cun Hui Zhang.
Annals of Statistics (2010)

3129 Citations

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)

918 Citations

The sparsity and bias of the Lasso selection in high-dimensional linear regression

Cun Hui Zhang;Jian Huang.
Annals of Statistics (2008)

918 Citations

Adaptive Lasso for sparse high-dimensional regression models

Jian Huang;Shuangge Ma;Cun Hui Zhang.
Statistica Sinica (2008)

643 Citations

Scaled sparse linear regression

Tingni Sun;Cun Hui Zhang.
Biometrika (2012)

506 Citations

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)

501 Citations

Optimal rates of convergence for covariance matrix estimation

T. Tony Cai;Cun Hui Zhang;Harrison H. Zhou.
Annals of Statistics (2010)

490 Citations

A group bridge approach for variable selection

Jian Huang;Shuange Ma;Huiliang Xie;Cun Hui Zhang.
Biometrika (2009)

356 Citations

A General Theory of Concave Regularization for High-Dimensional Sparse Estimation Problems

Cun-Hui Zhang;Tong Zhang.
Statistical Science (2012)

329 Citations

Fourier Methods for Estimating Mixing Densities and Distributions

Cun-Hui Zhang.
Annals of Statistics (1990)

308 Citations

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