1 citations · 1 across the 6 of their papers we have counts for
6 papers
Spike Estimation from Heteroscedastic Noise via Random Splitting
Zhigang Bao, Kha Man Cheong, Yuji Li +1
In this paper, we consider a spiked Wigner type matrix with a heteroscedastic and unknown variance profile. It is well known that in the supercritical regime of the BBP transition,…
A spectral approach for online covariance change point detection
Zhigang Bao, Kha Man Cheong, Yuji Li +1
Change point detection in covariance structures is a fundamental and crucial problem for sequential data. Under the high-dimensional setting, most of the existing research has focu…
On the adaptive deterministic block coordinate descent methods with momentum for solving large linear least-squares problems
Long-Ze Tan, Ming-Yu Deng, Jia-Li Qiu +1
In this work, we first present an adaptive deterministic block coordinate descent method with momentum (mADBCD) to solve the linear least-squares problem, which is based on Polyak'…
On eigenvalues of sample covariance matrices based on high dimensional compositional data
Qianqian Jiang, Jiaxin Qiu, Zeng Li
This paper studies the asymptotic spectral properties of the sample covariance matrix for high dimensional compositional data, including the limiting spectral distribution, the lim…
Robust estimation for number of factors in high dimensional factor modeling via Spearman correlation matrix
Jiaxin Qiu, Zeng Li, Jianfeng Yao
Determining the number of factors in high-dimensional factor modeling is essential but challenging, especially when the data are heavy-tailed. In this paper, we introduce a new est…
Asymptotic normality for eigenvalue statistics of a general sample covariance matrix when and applications
Jiaxin Qiu, Zeng Li, Jianfeng Yao
The asymptotic normality for a large family of eigenvalue statistics of a general sample covariance matrix is derived under the ultra-high dimensional setting, that is, when the di…