2 citations · 3 across the 2 of their papers we have counts for
2 papers
cs.LG2019★ 2 cited
Robust Linear Discriminant Analysis Using Ratio Minimization of L1,2-Norms
Feiping Nie, Hua Wang, Zheng Wang +1
As one of the most popular linear subspace learning methods, the Linear Discriminant Analysis (LDA) method has been widely studied in machine learning community and applied to many…
cs.LG2019★ 1 cited
Spherical Principal Component Analysis
Kai Liu, Qiuwei Li, Hua Wang +1
Principal Component Analysis (PCA) is one of the most important methods to handle high dimensional data. However, most of the studies on PCA aim to minimize the loss after projecti…