3 papers
cs.LG2025
Spectral Perturbation Bounds for Low-Rank Approximation with Applications to Privacy
Phuc Tran, Nisheeth K. Vishnoi, Van H. Vu
A central challenge in machine learning is to understand how noise or measurement errors affect low-rank approximations, particularly in the spectral norm. This question is especia…
math.NA2025
Davis-Kahan Theorem under a moderate gap condition
Phuc Tran, Van Vu
The classical Davis-Kahan theorem provides an efficient bound on the perturbation of eigenspaces of a matrix under a large (eigenvalue) gap condition. In this paper, we consider th…
math.SP2024
New matrix perturbation bounds with relative norm: Perturbation of eigenspaces
Phuc Tran, Van Vu
Matrix perturbation bounds (such as Weyl and Davis-Kahan) are used abundantly in many areas of mathematics and data science. Many bounds (such as the above two) involve the spectra…