11 citations · 19 across the 9 of their papers we have counts for
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cs.LG2019★ 3 cited
Learning Feature Sparse Principal Components
Lai Tian, Feiping Nie, Xuelong Li
This paper presents new algorithms to solve the feature-sparsity constrained PCA problem (FSPCA), which performs feature selection and PCA simultaneously. Existing optimization met…
cs.LG2016★ 11 cited
Non-Greedy L21-Norm Maximization for Principal Component Analysis
Feiping Nie, Heng Huang
Principal Component Analysis (PCA) is one of the most important unsupervised methods to handle high-dimensional data. However, due to the high computational complexity of its eigen…