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Pré-Publication, Document De Travail Année : 2023

Randomized Householder QR

Résumé

This paper introduces a randomized Householder QR factorization (RHQR). This factorization can be used to obtain a well conditioned basis of a set of vectors and thus can be employed in a variety of applications. We discuss in particular the usage of this randomized Householder factorization in the Arnoldi process. Numerical experiments show that RHQR produces a well conditioned basis and an accurate factorization. We observe that for some cases, it can be more stable than Randomized Gram-Schmidt (RGS) in single precision.
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Dates et versions

hal-04156310 , version 1 (07-07-2023)
hal-04156310 , version 2 (12-07-2023)
hal-04156310 , version 3 (28-07-2023)
hal-04156310 , version 4 (03-03-2024)

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  • HAL Id : hal-04156310 , version 1

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Laura Grigori, Edouard Timsit. Randomized Householder QR. 2023. ⟨hal-04156310v1⟩
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