16 citations · 57 across the 20 of their papers we have counts for
8 papers · 1 filter
Impact of signal-to-noise ratio and bandwidth on graph Laplacian spectrum from high-dimensional noisy point cloud
Xiucai Ding, Hau-Tieng Wu
We systematically study the spectrum of kernel-based graph Laplacian (GL) constructed from high-dimensional and noisy random point cloud in the nonnull setup. The problem is motive…
Statistical inference for principal components of spiked covariance matrices
Zhigang Bao, Xiucai Ding, Jingming Wang +1
In this paper, we study the asymptotic behavior of the extreme eigenvalues and eigenvectors of the high dimensional spiked sample covariance matrices, in the supercritical case whe…
Globally Optimal And Adaptive Short-Term Forecast of Locally Stationary Time Series And A Test for Its Stability
Xiucai Ding, Zhou Zhou
Forecasting the evolution of complex systems is one of the grand challenges of modern data science. The fundamental difficulty lies in understanding the structure of the observed s…
On the spectral property of kernel-based sensor fusion algorithms of high dimensional data
Xiucai Ding, Hau-Tieng Wu
We apply local laws of random matrices and free probability theory to study the spectral properties of two kernel-based sensor fusion algorithms, nonparametric canonical correlatio…
Principal components of spiked covariance matrices in the supercritical regime
Zhigang Bao, Xiucai Ding, Jingming Wang +1
In this paper, we study the asymptotic behavior of the extreme eigenvalues and eigenvectors of the spiked covariance matrices, in the supercritical regime. Specifically, we derive…
Singular vector and singular subspace distribution for the matrix denoising model
Zhigang Bao, Xiucai Ding, Ke Wang
In this paper, we study the matrix denosing model , where is a low-rank deterministic signal matrix and is a random noise matrix, and both are . In the sc…
Estimation and inference for precision matrices of non-stationary time series
Xiucai Ding, Zhou Zhou
In this paper, we consider the estimation and inference of precision matrices of a rich class of locally stationary and nonlinear time series assuming that only one realization of…
High dimensional deformed rectangular matrices with applications in matrix denoising
Xiucai Ding
We consider the recovery of a low rank matrix from its noisy observation in two different regimes. Under the assumption that is comparable to ,…