Sparse General Non-Negative Matrix Factorization Based on Left Semi-Tensor Product

Sparse General Non-Negative Matrix Factorization Based on Left Semi-Tensor Product

The dimension reduction of large scale high-dimensional data is a challenging task, especially the dimension reduction of face data and the accuracy increment of face recognition in the large scale face recognition system, which may cause large storage space and long recognition time. In order to fu...

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Bibliographic Details
Main Authors: Zigang Chen, Lixiang Li, Haipeng Peng, Yuhong Liu, Haihua Zhu, Yixian Yang
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Machine learning
unsupervised learning
semi-tensor product (STP)
sparse general non-negative matrix factorization (SGNMF)
Online Access:https://ieeexplore.ieee.org/document/8742644/

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