World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
45
Citations
48922
World Ranking
1406
National Ranking
618

Engineering and Technology

D-Index
43
Citations
48521
World Ranking
5970
National Ranking
1649

Research.com Recognitions

  • 2019 - Fellow of the American Statistical Association (ASA)

Overview

Hui Zou is affiliated with the University of Minnesota in the United States and has contributed extensively to research spanning computer science and mathematics. Their work includes publications primarily focused on statistics, machine learning, and related computational methods.

Their recent papers include the following:

  • Sparse Composite Quantile Regression in Ultrahigh Dimensions With Tuning Parameter Calibration (2020), published in IEEE Transactions on Information Theory
  • Unsupervised adversarial domain adaptation based on interpolation image for fish detection in aquaculture (2022), published in Computers and Electronics in Agriculture
  • Robust supervised multi-view feature selection with weighted shared loss and maximum margin criterion (2021), published in Knowledge-Based Systems
  • An Alternating Manifold Proximal Gradient Method for Sparse Principal Component Analysis and Sparse Canonical Correlation Analysis (2020), published in INFORMS Journal on Optimization
  • Retargeted multi-view classification via structured sparse learning (2022), published in Signal Processing

Frequent co-authors collaborating with Hui Zou include:

  • Ping Zhong
  • Le Zhou
  • Boxiang Wang
  • Yuwen Gu
  • Zhencai Shen

The venues where Hui Zou has published most often are:

  • arXiv (Cornell University)
  • Journal of the American Statistical Association
  • Statistica Sinica
  • IEEE Transactions on Information Theory
  • Stat

Their main fields of study include:

  • Computer Science
  • Mathematics

Within these, the subfields Hui Zou has worked in are:

  • Statistics and Probability
  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Computational Mechanics
  • Molecular Biology

The primary topics covered in their work are:

  • Statistical Methods and Inference
  • Face and Expression Recognition
  • Sparse and Compressive Sensing Techniques
  • Advanced Statistical Methods and Models
  • Statistical Methods and Bayesian Inference
  • Bayesian Methods and Mixture Models
  • Machine Learning and ELM

Hui Zou has received recognition as a Fellow of the American Statistical Association (ASA) in 2019.

Best Publications

  • Regularization and variable selection via the elastic net

    Hui Zou;Trevor Hastie

  • The adaptive lasso and its oracle properties

    Hui Zou

  • Sparse Principal Component Analysis

    Hui Zou;Trevor Hastie;Robert Tibshirani

  • Multi-class AdaBoost ∗

    Trevor Hastie;Saharon Rosset;Ji Zhu;Hui Zou

  • One-step Sparse Estimates in Nonconcave Penalized Likelihood Models.

    Hui Zou;Runze Li

  • On the “degrees of freedom” of the lasso

    Hui Zou;Trevor Hastie;Robert Tibshirani

  • On the adaptive elastic-net with a diverging number of parameters

    Hui Zou;Hao Helen Zhang

  • Addendum: Regularization and variable selection via the elastic net

    Hui Zou;Trevor Hastie

  • Composite quantile regression and the oracle model selection theory

    Y. Hui Zou;Ming Yuan

  • Regularized rank-based estimation of high-dimensional nonparanormal graphical models

    Lingzhou Xue;Hui Zou

  • NEW EFFICIENT ESTIMATION AND VARIABLE SELECTION METHODS FOR SEMIPARAMETRIC VARYING-COEFFICIENT PARTIALLY LINEAR MODELS

    Bo Kai;Runze Li;Hui Zou

  • Combining time series models for forecasting

    Hui Zou;Yuhong Yang

  • Strong oracle optimality of folded concave penalized estimation

    Jianqing Fan;Lingzhou Xue;Hui Zou

  • The doubly regularized support vector machine

    Li Wang;Ji Zhu;Hui Zou

  • A fast unified algorithm for solving group-lasso penalize learning problems

    Yi Yang;Hui Zou

  • Local composite quantile regression smoothing: an efficient and safe alternative to local polynomial regression

    Bo Kai;Runze Li;Hui Zou

  • Hybrid huberized support vector machines for microarray classification and gene selection

    Li Wang;Ji Zhu;Hui Zou

  • A direct approach to sparse discriminant analysis in ultra-high dimensions

    Qing Mai;Hui Zou;Ming Yuan

  • Positive-Definite ℓ1-Penalized Estimation of Large Covariance Matrices

    Lingzhou Xue;Shiqian Ma;Hui Zou

  • Statistical Foundations of Data Science

    Jianqing Fan;Runze Li;Cun-Hui Zhang;Hui Zou

  • Sparse precision matrix estimation via lasso penalized D-trace loss

    Teng Zhang;Hui Zou

Frequent Co-Authors

Trevor Hastie
Trevor Hastie Stanford University
Shiqian Ma
Shiqian Ma Rice University
Ming Yuan
Ming Yuan Columbia University
Runze Li
Runze Li Pennsylvania State University
Hao Helen Zhang
Hao Helen Zhang University of Arizona
Jianqing Fan
Jianqing Fan Princeton University
Han Liu
Han Liu Northwestern University
Robert Tibshirani
Robert Tibshirani Stanford University
Saharon Rosset
Saharon Rosset Tel Aviv University
Sudipto Banerjee
Sudipto Banerjee University of California, Los Angeles

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