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performances of SVM and LR in sparse NMF, NMF with MU and ALS
Comparison of time of different algorithms
performances of SVM and LR in sparse NMF, NMF with MU and ALS
FACE GENDER RECOGNITION
Learning Part-based Dictionary by Spare NMF
Studied different variants of non-negative matrix factorization (NMF) algorithms including multiplicative update method and alternating least squares method
Presented the framework of NMF and a sparse version of NMF algorithm to learn a part-based dictionary for data
representation
Conducted experiments to compare the performance of different NMF variant in terms of support vector machine (SVM) and logistic regression classification accuracies and the speeds
Face Gender Recognition: Projects
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