Learning Feature Sparse Principal Components

23 Apr 2019Lai TianFeiping NieXuelong Li

This paper presents new algorithms to solve the feature-sparsity constrained PCA problem (FSPCA), which performs feature selection and PCA simultaneously. Existing optimization methods for FSPCA require data distribution assumptions and are lack of global convergence guarantee... (read more)

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