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
35 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
21 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