A New Discriminative Sparse Representation Method for Robust Face Recognition via l2 Regularization

IEEE Transactions on Neural Networks and Learning Systems(2017)

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摘要
Sparse representation has shown an attractive performance in a number of applications. However, the available sparse representation methods still suffer from some problems, and it is necessary to design more efficient methods. Particularly, to design a computationally inexpensive, easily solvable, and robust sparse representation method is a significant task. In this paper, we explore the issue of...
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关键词
Training,Linear programming,Robustness,Face recognition,Algorithm design and analysis,Closed-form solutions,Matching pursuit algorithms
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