3 papers
math.ST2025
Estimating Multiple Weighted Networks with Node-Sparse Differences and Shared Low-Rank Structure
Hao Yan, Keith Levin
We study the problem of modeling multiple symmetric, weighted networks defined on a common set of nodes, where networks arise from different groups or conditions. We propose a mode…
math.ST2025
Improved dependence on coherence in eigenvector and eigenvalue estimation error bounds
Hao Yan, Keith Levin
Spectral estimators are fundamental in lowrank matrix models and arise throughout machine learning and statistics, with applications including network analysis, matrix completion a…
math.ST2024
Coherence-free Entrywise Estimation of Eigenvectors in Low-rank Signal-plus-noise Matrix Models
Hao Yan, Keith Levin
Spectral methods are widely used to estimate eigenvectors of a low-rank signal matrix subject to noise. These methods use the leading eigenspace of an observed matrix to estimate t…