51 citations · 77 across the 6 of their papers we have counts for
6 papers
Principal Component Analysis Based on T-norm Maximization
Xiang-Fei Yang, Yuan-Hai Shao, Chun-Na Li +2
Classical principal component analysis (PCA) may suffer from the sensitivity to outliers and noise. Therefore PCA based on -norm and -norm () have been s…
Multiple Flat Projections for Cross-manifold Clustering
Lan Bai, Yuan-Hai Shao, Wei-Jie Chen +2
Cross-manifold clustering is a hard topic and many traditional clustering methods fail because of the cross-manifold structures. In this paper, we propose a Multiple Flat Projectio…
Single and Union Non-parallel Support Vector Machine Frameworks
Chun-Na Li, Yuan-Hai Shao, Huajun Wang +4
Considering the classification problem, we summarize the nonparallel support vector machines with the nonparallel hyperplanes to two types of frameworks. The first type constructs…
Robust Bhattacharyya bound linear discriminant analysis through adaptive algorithm
Chun-Na Li, Yuan-Hai Shao, Zhen Wang +1
In this paper, we propose a novel linear discriminant analysis criterion via the Bhattacharyya error bound estimation based on a novel L1-norm (L1BLDA) and L2-norm (L2BLDA). Both L…
Generalized two-dimensional linear discriminant analysis with regularization
Chun-Na Li, Yuan-Hai Shao, Wei-Jie Chen +2
Recent advances show that two-dimensional linear discriminant analysis (2DLDA) is a successful matrix based dimensionality reduction method. However, 2DLDA may encounter the singul…
Insensitive Stochastic Gradient Twin Support Vector Machine for Large Scale Problems
Zhen Wang, Yuan-Hai Shao, Lan Bai +2
Stochastic gradient descent algorithm has been successfully applied on support vector machines (called PEGASOS) for many classification problems. In this paper, stochastic gradient…