Refines subspace preconditioning for randomized linear solvers via QR-like factorization, enabling implicit use and proving expected linear convergence while reducing to a smaller system with good singular values.
Adaptive randomized pivoting and volume sampling
1 Pith paper cite this work. Polarity classification is still indexing.
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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.
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math.NA 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
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On subspace-constrained preconditioning for randomized iterative methods
Refines subspace preconditioning for randomized linear solvers via QR-like factorization, enabling implicit use and proving expected linear convergence while reducing to a smaller system with good singular values.