Adaptive Randomized Pivoting for Column Subset Selection, DEIM, and Low-Rank Approximation

Authors

Alice Cortinovis (ORCID: https://orcid.org/0000-0001-6917-5106)
Daniel Kreßner (ORCID: https://orcid.org/0000-0003-3369-2958)

Institutions

University of Pisa (IT)
École Polytechnique Fédérale de Lausanne (CH)

Publication Details

Journal: SIAM Journal on Matrix Analysis and Applications
Published: 2026-01-02
DOI: https://doi.org/10.1137/24m1719189
Primary Topic: Stochastic Gradient Optimization Techniques
Type: article
Field-Weighted Citation Impact: 0.00

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article

Adaptive Randomized Pivoting for Column Subset Selection, DEIM, and Low-Rank Approximation

Alice Cortinovis, Daniel Kreßner

Jan 2, 2026

SIAM Journal on Matrix Analysis and Applications

Stochastic Gradient Optimization Techniques

article

Adaptive Randomized Pivoting for Column Subset Selection, DEIM, and Low-Rank Approximation

Alice Cortinovis, Daniel Kreßner

January 2, 2026article en

Abstract

No abstract available for this paper.

SIAM Journal on Matrix Analysis and ApplicationsVol. 47(1)

University of Pisa (IT), École Polytechnique Fédérale de Lausanne (CH)

Openalex Percentile: Top 98%

Stochastic Gradient Optimization Techniques

DOI Open Access PDF OpenAlex

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Adaptive Randomized Pivoting for Column Subset Selection, DEIM, and Low-Rank Approximation — Alice Cortinovis, Daniel Kreßner · SIAM Journal on Matrix Analysis and Applications (2026) | TGRS Research Map | TGRS