| Identifying the number of factors from singular values of a large sample auto-covariance matrix Z Li, Q Wang, J Yao | 45 | 2017 |
| On testing for high-dimensional white noise Z Li, C Lam, J Yao, Q Yao | 34 | 2019 |
| On singular value distribution of large-dimensional autocovariance matrices Z Li, G Pan, J Yao Journal of Multivariate Analysis 137, 119-140, 2015 | 23 | 2015 |
| Asymptotic joint distribution of extreme eigenvalues and trace of large sample covariance matrix in a generalized spiked population model Z Li, F Han, J Yao The Annals of Statistics 48 (6), 3138-3160, 2020 | 20 | 2020 |
| Non‐Parametric Estimation of High‐Frequency Spot Volatility for Brownian Semimartingale with Jumps C Yu, Y Fang, Z Li, B Zhang, X Zhao Journal of Time Series Analysis 35 (6), 572-591, 2014 | 16 | 2014 |
| Central limit theorem for linear spectral statistics of large dimensional Kendall’s rank correlation matrices and its applications Z Li, Q Wang, R Li The Annals of Statistics 49 (3), 1569-1593, 2021 | 15 | 2021 |
| Testing the sphericity of a covariance matrix when the dimension is much larger than the sample size Z Li, J Yao | 14 | 2016 |
| Self-constrained inference optimization on structural groups for human pose estimation Z Kan, S Chen, Z Li, Z He European Conference on Computer Vision, 729-745, 2022 | 12 | 2022 |
| Asymptotic normality for eigenvalue statistics of a general sample covariance matrix when and applications J Qiu, Z Li, J Yao The Annals of Statistics 51 (3), 1427-1451, 2023 | 6 | 2023 |
| Provable more data hurt in high dimensional least squares estimator Z Li, C Xie, Q Wang arXiv preprint arXiv:2008.06296, 2020 | 6 | 2020 |
| Joint central limit theorem for eigenvalue statistics from several dependent large dimensional sample covariance matrices with application W Li, Z Li, J Yao Scandinavian Journal of Statistics 45 (3), 699-728, 2018 | 5 | 2018 |
| Asymptotic normality and confidence intervals for prediction risk of the min-norm least squares estimator Z Li, C Xie, Q Wang International Conference on Machine Learning, 6533-6542, 2021 | 3 | 2021 |
| On eigenvalues of a high-dimensional Kendall’s rank correlation matrix with dependence Z Li, C Wang, Q Wang Science China Mathematics 66 (11), 2615-2640, 2023 | 2 | 2023 |
| Heavy-tailed regularization of weight matrices in deep neural networks X Xiao, Z Li, C Xie, F Zhou International Conference on Artificial Neural Networks, 236-247, 2023 | 2 | 2023 |
| On eigenvalues of a high dimensional Kendall's rank correlation matrix with dependences C Wang, Q Wang, Z Li arXiv e-prints, arXiv: 2109.13624, 2021 | 1 | 2021 |
| On eigenvalues of sample covariance matrices based on high dimensional compositional data Q Jiang, J Qiu, Z Li arXiv preprint arXiv:2312.14420, 2023 | | 2023 |
| Robust estimation for number of factors in high dimensional factor modeling via Spearman correlation matrix J Qiu, Z Li, J Yao arXiv preprint arXiv:2309.00870, 2023 | | 2023 |
Jianfeng (Jeff) YaoThe Chinese University of Hong Kong (Shenzhen)在 cuhk.edu.cn 的電子郵件地址已通過驗證
