Randomized matrix computations: Themes and variations
<|reference_start|>Randomized matrix computations: Themes and variations: This short course offers a new perspective on randomized algorithms for matrix computations. It explores the distinct ways in which probability can be used to design algorithms for numerical linear algebra. Each design template is illustrated by its application to several computational problems. This treatment establishes conceptual foundations for randomized numerical linear algebra, and it forges links between algorithms that may initially seem unrelated.<|reference_end|>
@article{kireeva2024randomized,
    title={Randomized matrix computations: Themes and variations},
    author={Anastasia Kireeva and Joel A. Tropp},
    journal={arXiv preprint arXiv:2402.17873},
    year={2024},
    doi={10.7907/7yade-5k351},
    number={Caltech CMS Lecture Notes 2023-02},
    archivePrefix={arXiv},
    eprint={2402.17873},
    primaryClass={math.NA cs.NA math.PR}
}