V. Vu

collaborators

3 papers

math.NA2026

Matrices perturbed by random noise: The accuracy of low-rank approximation

Phuc Tran, Van Vu

Let $A$ be an $m \times n$ matrix with rank $r$ and singular value decomposition $A = \sum_{i = 1}^{r} σ_{i} u_{i} v_{i}^{⊤},$ where the $σ_{i}$ are its singular values, ordered decreasingl…

math.PR2026

Anti-concentration with respect to random permutations

Aaron Berger, Ross Berkowitz, Pat Devlin +1

Classical anti-concentration results focus on the random sum $S := \sum_{i = 1}^{n} I^¾_{i} v_{i}$ , where $I^¾_{i}$ are independent random variables and $v_{i}$ are real numbers. In this paper,…

math.ST2025

Fast exact recovery of noisy matrix from few entries: the infinity norm approach

BaoLinh Tran, Van Vu

The matrix recovery (completion) problem, a central problem in data science and theoretical computer science, is to recover a matrix $A$ from a relatively small sample of entries.…