16 citations · 46 across the 15 of their papers we have counts for
15 papers
Geometric bias in eigenspace perturbation under random heterogeneous noise
Fengkai Liu, Ke Wang, Wanjie Wang
Spectral methods rely on the stability of principal eigenspaces under random perturbations. Classically, this is quantified by the Davis-Kahan and Wedin theorems, which bound the e…
On a Class of Nonlocal SIR Models
Li, Guan, Dong Li +2
We revisit the classic Susceptible-Infected-Recovered (SIR) epidemic model and one of its nonlocal variations recently developed in \cite{Guan}. We introduce several new approaches…
Symmetric radial decreasing rearrangement can increase the fractional Gagliardo norm in domains
Dong Li, Ke Wang
We show that the symmetric radial decreasing rearrangement can increase the fractional Gagliardo semi-norm in domains.
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…
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…
Enhanced Expressive Power and Fast Training of Neural Networks by Random Projections
Jian-Feng Cai, Dong Li, Jiaze Sun +1
Random projections are able to perform dimension reduction efficiently for datasets with nonlinear low-dimensional structures. One well-known example is that random matrices embed…