Randomized Algorithms for Matrices and Massive Data Sets

Summary: Randomized sampling algorithms reveal structure in massive matrices and tensors. A tutorial blending provable guarantees with scalable applications to large biological and internet datasets. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 9619
Venue: VLDB
Year: 2006
Pagerank: -
Overall Rank: 13,841 | 5.04%
DOI: -

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Authors

1. Petros Drineas (Rensselaer Polytechnic Institute)
2. Michael W. Mahoney (Yahoo)

BibTeX Citation

@article{drineas_vldb06,
        title = {{Randomized Algorithms for Matrices and Massive Data Sets}},
        author = {Drineas, Petros and Mahoney, Michael W.},
        journal = {PVLDB},
        series = {{VLDB} '06},
        pages = {1269},
        year = {2006}
}

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