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Adaptive randomized pivoting and volume sampling

Machine Learning 2026-04-06 v2 Data Structures and Algorithms Machine Learning Numerical Analysis Numerical Analysis Computation

Abstract

Adaptive randomized pivoting (ARP) is a recently proposed and highly effective algorithm for column subset selection. This paper reinterprets the ARP algorithm by drawing connections to the volume sampling distribution and active learning algorithms for linear regression. As consequences, this paper presents new analysis for the ARP algorithm and faster implementations using rejection sampling.

Keywords

Cite

@article{arxiv.2510.02513,
  title  = {Adaptive randomized pivoting and volume sampling},
  author = {Ethan N. Epperly},
  journal= {arXiv preprint arXiv:2510.02513},
  year   = {2026}
}

Comments

14 pages, 2 figures

R2 v1 2026-07-01T06:14:16.724Z