Data provided by National Institute of Standards and Technology
A unified, multi-language library implementing randomized algorithms for low-rank matrix factorizations of both real and complex matrices. The library provides efficient randomized sketching-based methods for large-scale matrix decompositions with consistent APIs across Python, MATLAB/Octave, and Julia.
About this Dataset
Updated: 2026-09-04
Metadata Last Updated:
2026-01-23 00:00:00
Date Created:
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| Title | librla: A library of randomized linear algebra routines |
|---|---|
| Description | A unified, multi-language library implementing randomized algorithms for low-rank matrix factorizations of both real and complex matrices. The library provides efficient randomized sketching-based methods for large-scale matrix decompositions with consistent APIs across Python, MATLAB/Octave, and Julia. |
| Modified | 2026-01-23 00:00:00 |
| Publisher Name | National Institute of Standards and Technology |
| Contact | mailto:[email protected] |
| Keywords | Randomized methods , QR factorization , singular value decomposition , interpolatory decomposition , Python , Matlab/Octave , Julia |
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"fn": "Zydrunas Gimbutas"
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"title": "librla: A library of randomized linear algebra routines",
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