Rank 2r Iterative Least Squares: Efficient Recovery of III-Conditioned Low Rank Matrices from Few Entries.

Bauch J, Nadler B, Zilber P

DOI: 10.1137/20m1315294
Published: 2021
Container: SIAM journal on mathematics of data science
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1137/20m1315294,
  title = {Rank 2r Iterative Least Squares: Efficient Recovery of III-Conditioned Low Rank Matrices from Few Entries.},
  author = {Bauch J and Nadler B and Zilber P},
  year = {2021},
  journal = {SIAM journal on mathematics of data science},
  doi = {10.1137/20m1315294},
  url = {https://doi.org/10.1137/20m1315294}
}

RIS

TY  - JOUR
TI  - Rank 2r Iterative Least Squares: Efficient Recovery of III-Conditioned Low Rank Matrices from Few Entries.
AU  - Bauch J
AU  - Nadler B
AU  - Zilber P
PY  - 2021
JO  - SIAM journal on mathematics of data science
DO  - 10.1137/20m1315294
UR  - https://doi.org/10.1137/20m1315294
ER  -

APA

J, B., B, N., & P, Z. (2021). Rank 2r Iterative Least Squares: Efficient Recovery of III-Conditioned Low Rank Matrices from Few Entries.. SIAM journal on mathematics of data science. https://doi.org/10.1137/20m1315294

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pubmed · retrieved 2026-09-25T09:00:19.234Z