Sparse general non-negative matrix factorization based on left semi-tensor product

HIGHLIGHTS

• who: Sparse General Non-Negative Matrix et al. from the of Artificial Intelligence, Tianjin University of Science and Technology, Tianjin, China have published the paper: Sparse General Non-Negative Matrix Factorization Based on Left Semi-Tensor Product, in the Journal: (JOURNAL) of December/14,/2016
• what: To further reduce the recognition time and the storage space in the large scale face recognition systems on the basis of the factorization based on left (GNMFL) without dimension matching constraints proposed in the previous work the authors propose a GNMFL/L (SGNMFL/L) to decompose a large number . . .
  

   

  

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