research
∙
09/02/2023
Robust estimation for number of factors in high dimensional factor modeling via Spearman correlation matrix
Determining the number of factors in high-dimensional factor modeling is...
share
research
∙
04/06/2023
Heavy-Tailed Regularization of Weight Matrices in Deep Neural Networks
Unraveling the reasons behind the remarkable success and exceptional gen...
research
∙
02/06/2023
Network Autoregression for Incomplete Matrix-Valued Time Series
We study the dynamics of matrix-valued time series with observed network...
research
∙
07/06/2022
Self-Constrained Inference Optimization on Structural Groups for Human Pose Estimation
We observe that human poses exhibit strong group-wise structural correla...
research
∙
02/25/2022
On singular values of large dimensional lag-tau sample autocorrelation matrices
We study the limiting behavior of singular values of a lag-τ sample auto...
research
∙
09/28/2021
On eigenvalues of a high dimensional Kendall's rank correlation matrix with dependences
This paper investigates limiting spectral distribution of a high-dimensi...
research
∙
09/14/2021
Asymptotic normality for eigenvalue statistics of a general sample covariance matrix when p/n →∞ and applications
The asymptotic normality for a large family of eigenvalue statistics of ...
research
∙
06/18/2021
Sparse Linear Spectral Unmixing of Hyperspectral images using Expectation-Propagation
This paper presents a novel Bayesian approach for hyperspectral image un...
research
∙
08/14/2020
Provable More Data Hurt in High Dimensional Least Squares Estimator
This paper investigates the finite-sample prediction risk of the high-di...
research
∙
12/13/2019
Central Limit Theorem for Linear Spectral Statistics of Large Dimensional Kendall's Rank Correlation Matrices and its Applications
This paper is concerned with the limiting spectral behaviors of large di...
research
∙
06/23/2019
Asymptotic joint distribution of extreme eigenvalues and trace of large sample covariance matrix in a generalized spiked population model
This paper studies the joint limiting behavior of extreme eigenvalues an...
research
∙
08/10/2018
On testing for high-dimensional white noise
Testing for white noise is a classical yet important problem in statisti...
research
∙
01/20/2018
