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Efficient matrix completion with Gaussian models

Publication ,  Journal Article
Léger, F; Yu, G; Sapiro, G
Published in: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
August 18, 2011

A general framework based on Gaussian models and a MAPEM algorithm is introduced in this paper for solving matrix/ table completion problems. The numerical experiments with the standard and challenging movie ratings data show that the proposed approach, based on probably one of the simplest probabilistic models, leads to the results in the same ballpark as the state-of-the-art, at a lower computational cost. © 2011 IEEE.

Duke Scholars

Published In

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

DOI

ISSN

1520-6149

Publication Date

August 18, 2011

Start / End Page

1113 / 1116
 

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Léger, F., Yu, G., & Sapiro, G. (2011). Efficient matrix completion with Gaussian models. ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, 1113–1116. https://doi.org/10.1109/ICASSP.2011.5946603
Léger, F., G. Yu, and G. Sapiro. “Efficient matrix completion with Gaussian models.” ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, August 18, 2011, 1113–16. https://doi.org/10.1109/ICASSP.2011.5946603.
Léger F, Yu G, Sapiro G. Efficient matrix completion with Gaussian models. ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. 2011 Aug 18;1113–6.
Léger, F., et al. “Efficient matrix completion with Gaussian models.” ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, Aug. 2011, pp. 1113–16. Scopus, doi:10.1109/ICASSP.2011.5946603.
Léger F, Yu G, Sapiro G. Efficient matrix completion with Gaussian models. ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. 2011 Aug 18;1113–1116.

Published In

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

DOI

ISSN

1520-6149

Publication Date

August 18, 2011

Start / End Page

1113 / 1116