@inproceedings{4c4162783b2242a38a09e8547c14d79a,

title = "Non-negative tensor factorization with applications to statistics and computer vision",

abstract = "We derive algorithms for finding a non-negative n-dimensional tensor factorization (n-NTF) which includes the non-negative matrix factorization (NMF) as a particular case when n = 2. We motivate the use of n-NTF in three areas of data analysis: (i) connection to latent class models in statistics, (ii) sparse image coding in computer vision, and (iii) model selection problems. We derive a {"}direct{"} positive-preserving gradient descent algorithm and an alternating scheme based on repeated multiple rank-1 problems.",

author = "Amnon Shashua and Tamir Hazan",

year = "2005",

language = "American English",

isbn = "1595931805",

series = "ICML 2005 - Proceedings of the 22nd International Conference on Machine Learning",

pages = "793--800",

editor = "L. Raedt and S. Wrobel",

booktitle = "ICML 2005 - Proceedings of the 22nd International Conference on Machine Learning",

note = "ICML 2005: 22nd International Conference on Machine Learning ; Conference date: 07-08-2005 Through 11-08-2005",

}