An efficient method for non-negative low-rank completion
Author:
Funder
MIUR
Publisher
Springer Science and Business Media LLC
Subject
Applied Mathematics,Computational Mathematics
Link
http://link.springer.com/content/pdf/10.1007/s10444-020-09779-x.pdf
Reference27 articles.
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2. Ang, A.M.S., Gillis N.: Algorithms and comparisons of non-negative matrix factorization with volume regularization for hyperspectral unmixing. arXiv:1903.04362 (2019)
3. Bennet, J., Lanning, S.: The netflix prize. In: Proceedings of the KKD cup and workshop. San Jose, CA, USA, 12 August 2007, pp. 35 (2007)
4. Berman, A., Plemmons, R.J.: Nonnegative matrices in the mathematical sciences. Classics in Applied Mathematics Society for Industrial and Applied Mathematics (SIAM), Philadelphia (1994)
5. Brand, M.: Incremental singular value decomposition of uncertain data with missing values. In: European conference on computer vision. Lecture Notes in Computer Science, vol. 2350, pp 707–720. Springer, Berlin (2002)
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