Sparse non-negative tensor factorization using columnwise coordinate descent

@article{Liu2012SparseNT,
  title={Sparse non-negative tensor factorization using columnwise coordinate descent},
  author={Ji Liu and Jun Liu and Peter Wonka and Jieping Ye},
  journal={Pattern Recognition},
  year={2012},
  volume={45},
  pages={649-656}
}
Many applications in computer vision, biomedical informatics, and graphics deal with data in the matrix or tensor form. Non-negative matrix and tensor factorization, which extract data-dependent non-negative basis functions, have been commonly applied for the analysis of such data for data compression, visualization, and detection of hidden information (factors). In this paper, we present a fast and flexible algorithm for sparse non-negative tensor factorization (SNTF) based on columnwise… CONTINUE READING
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In Csiszar’s divergences for nonnegative matrix factorization Family of new algorithms, pages

  • A. Cichocki, R.Zdunek, S. Amari
  • 2006
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