The DOI matches its Crossref record.
Adaptive Sampling and Fast Low-Rank Matrix Approximation
Overview
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Citations
Cited by
Relative-Error $CUR$ Matrix Decompositions
Drineas, P., Mahoney, M. W., & Muthukrishnan, S. (2008) · SIAM Journal on Matrix Analysis and Applications · doi:10.1137/07070471x · Cited by 461
A Randomized Algorithm for Principal Component Analysis
Rokhlin, V., Szlam, A., & Tygert, M. (2010) · SIAM Journal on Matrix Analysis and Applications · doi:10.1137/080736417 · Cited by 422
A quantum-inspired classical algorithm for recommendation systems
Tang, E. (2019) · Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing · doi:10.1145/3313276.3316310 · Cited by 360
Numerical linear algebra in the streaming model
Clarkson, K. L., & Woodruff, D. P. (2009) · Proceedings of the forty-first annual ACM symposium on Theory of computing · doi:10.1145/1536414.1536445 · Cited by 301
Metadata
- Authors
- Deshpande, A., & Vempala, S.
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer Berlin Heidelberg
- Published
- 2006
- Volume
- 13
- Pages
- 292-303
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W2044610104
- Cited by
- 186
- References
- 0
- FWCI
- 8.47
- Type
- conference paper
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Adaptive Sampling and Fast Low-Rank Matrix Approximation. https://app.cochat.ai/papers/10.1007/11830924_28
- The paper
- Deshpande, A., & Vempala, S. (2006). Adaptive Sampling and Fast Low-Rank Matrix Approximation. Lecture Notes in Computer Science. https://doi.org/10.1007/11830924_28
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
