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Faculty

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LI Zeng
Associate Professor
0755-88015671

Research Interest:

  • Random Matrix Theory

  • High dimensional Statistics

  • Time Series Analysis

  • Machine Learning

 

Professional Experience:

Jan 2021-present, Department of Statistics and Data Science, Southern University of Science and Technology, Associate Professor

Aug 2019-Dec 2020, Department of Statistics and Data Science, Southern University of Science and Technology, Assistant Professor

Oct 2017-Aug 2019, Department of Statistics, Pennsylvania State University Eberly Postdoc Fellow, mentor: Prof. Runze Li

Apr 2017-Aug 2017, Department of Statistics, University of Washington, Seattle,Research Assistant, mentor: Dr. Fang Han

Sep 2012- Mar 2017, Department of Statistics and Actuarial Science, HKU, Teaching Assistant

 

Educational Background:

Apr 2017, The Unviersity of Hong Kong (HKU), Ph.D., Department of Statistics and Actuarial Science Advisor: Prof. Jianfeng Yao

Sep 2012, Renmin University of China, Beijing (RUC) M.Sc., School of Statistics

Sep 2009, Beijing Normal University, Beijing (BNU), B.Sc., School of Mathematical Science

 

Awards and Honors:

Sep 2012- Mar 2017, Department of Statistics And Actuarial Science, HKU Excellent Teaching Assistant Award (5 times)

 

Academic Services:

Referee Service. Annals of Statistics, JASA, Journal of the Royal Statistical Society: Series B, Biometrika, IEEE Transactions on information theory, IEEE Transactions on Signal Processing, Journal of Multivariate Analysis, IISE Transactions

 

Selected Publications:

  1. Jiaxin Qiu, Zeng Li*, Jianfeng Yao, (2024). Robust estimation for number of factors in high dimensional factor modeling via Spearman correlation matrix,  Journal of the American Statistical Association, to appear.

  2. Zeng Li, Cheng Wang*, Qinwen Wang (2023). On eigenvalues of a high-dimensional Kendall's rank correlation matrix with dependence. Science China Mathematics, 66, 2615-2640.

  3. Xuanzhe Xiao, Zeng Li*, Chuanlong Xie, Fengwei Zhou (2023).  Heavy-tailed regularization of weight matrices in deep neural networks. 32nd International Conferences on Artificial Neural Networks (ICANN), Sep 2023.

  4. Jiaxin Qiu, Zeng Li*, Jianfeng Yao (2023). Asymptotic normality for eigenvalue statistics of a general sample covariance matrix when p/n-> infinity and applications. The Annals of Statistics, 51(3), 1427-1451.

  5. Zhanting Long, Zeng Li*, Ruitao Lin, Jiaxin Qiu (2023). On singular values of large dimensional lag-tau sample auto-correlation matrices. Journal of Multivariate Analysis, 197, 105205.

  6. Zhehan Kan, Shuoshuo Chen, Zeng Li, Zhihai He* (2022). Self-supervised Reciprocal Learning and Optimization of Structural Groups for Human Pose Estimation, Proceedings of the 17th European Conference on Computer Vision (ECCV), 2022.

  7. Zeng Li, Qinwen Wang*, Runze Li (2021). Central limit theorem for linear spectral statistics of large dimensional Kendall's rank correlation matrices and its applications, The Annals of Statistics, 49(3), 1569-1593.

  8. Zeng Li, Qinwen Wang*, Chuanlong Xie, (2021). Asymptotic Normality and Confidence Intervals for Prediction Risk of the Min-norm Least Squares Estimator, in International Conference on Machine Learning (ICML), May 2021

  9. Zeng Li, Fang Han*, Jianfeng Yao (2020). Asymptotic joint distribution of extreme eigenvalues and trace of large sample covariance matrix in a generalized spiked population model, The Annals of Statistics, 48(6), 3138-3160.

  10. Zeng Li, Jianfeng Yao*, Clifford Lam, Qiwei Yao (2019). On testing for high-dimensional white noise, The Annals of Statistics, 47(6), 3382-3412.

  11. Weiming Li, Zeng Li, Jianfeng Yao* (2018). Joint CLT for linear spectral statistics of dependent large dimensional sample covariance matrices, Scandinavian Journal of Statistics, 45(3), 699-728.

  12. Zeng Li, Qinwen Wang, Jianfeng Yao* (2017). Identifying number of factors from singular values of lagged sample auto-covariance matrix, The Annals of Statistics, 45(1), 257-288.

  13. Zeng Li*, Jianfeng Yao (2016). Testing the sphericity of a covariance matrix when the dimension is much larger than the sample size, Electronic Journal of Statistics, 10(2), 2973-3010.

  14. Zeng Li, Guangming Pan, Jianfeng Yao* (2015). On singular value distribution of large-dimensional auto-covariance matrices, Journal of Multivariate Analysis, 137, 119-140.

  15. Chao Yu, Yue Fang*, Zeng Li, Bo Zhang, Xujie Zhao (2014). Nonparametric estimation of high frequency spot volatility for Brownian semimartingale with jumps, Journal of Time Series Analysis, 35(6), 572-591.


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