1 citations · 1 across the 6 of their papers we have counts for
6 papers
Multi-kernel spectral clustering: Entrywise eigenvector perturbation bounds and exact recovery
Zeqin Lin, Guangming Pan, Zhixiang Zhang +1
Kernel spectral clustering with a single bandwidth can be inadequate for data exhibiting multiple characteristic pairwise-distance scales, a problem particularly prevalent in the h…
Phase Transition of Spectral Fluctuations in Large Gram Matrices with a Variance Profile: A Unified Framework for Sparse CLTs
Rui Wang, Guangming Pan, Dandan Jiang
We study the asymptotic spectral behavior of high-dimensional random Gram matrices with sparsity and a variance profile, motivated by applications in wireless communications. Speci…
High-Dimensional Precision Matrix Quadratic Forms: Estimation Framework for
Shizhe Hong, Weiming Li, Guangming Pan
We propose a novel estimation framework for quadratic functionals of precision matrices in high-dimensional settings, particularly in regimes where the feature dimension exceed…
Simultaneous Detection and Localization of Mean and Covariance Changes in High Dimensions
Junfeng Cui, Guangming Pan, Guanghui Wang +1
Existing methods for high-dimensional changepoint detection and localization typically focus on changes in either the mean vector or the covariance matrix separately. This separati…
Eigenvector overlaps in large sample covariance matrices and nonlinear shrinkage estimators
Zeqin Lin, Guangming Pan
Consider a data matrix of size , where the columns are independent observations from a random vector with zero m…
Asymptotic distribution of spiked eigenvalues in the large signal-plus-noise models
Zeqin Lin, Guangming Pan, Peng Zhao +1
Consider large signal-plus-noise data matrices of the form , where is a low-rank deterministic signal matrix and the noise covariance matrix can be anisotrop…