Nonlinear Nonnegative Matrix Factorization Based on Discriminant Analysis with Application to Face Recognition

Abstract

Traditional Nonnegative Matrix Factorization (NMF) is a linear and unsupervised algorithm. This would limit the classification power of NMF for the complicated data. To overcome the above limitations of NMF, this paper proposes a novel supervised and nonlinear NMF algorithm based on kernel theory and discriminant analysis. We incorporate the class label… (More)
DOI: 10.1109/CIS.2015.54

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