51 citations · 103 across the 9 of their papers we have counts for
9 papers
Learning using granularity statistical invariants for classification
Ting-Ting Zhu, Yuan-Hai Shao, Chun-Na Li +1
Learning using statistical invariants (LUSI) is a new learning paradigm, which adopts weak convergence mechanism, and can be applied to a wider range of classification problems. Ho…
Nonlinear Kernel Support Vector Machine with 0-1 Soft Margin Loss
Ju Liu, Ling-Wei Huang, Yuan-Hai Shao +2
Recent advance on linear support vector machine with the 0-1 soft margin loss (-SVM) shows that the 0-1 loss problem can be solved directly. However, its theoretical and a…
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…
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…
A general model for plane-based clustering with loss function
Zhen Wang, Yuan-Hai Shao, Lan Bai +2
In this paper, we propose a general model for plane-based clustering. The general model contains many existing plane-based clustering methods, e.g., k-plane clustering (kPC), proxi…
Ramp-based Twin Support Vector Clustering
Zhen Wang, Xu Chen, Chun-Na Li +1
Traditional plane-based clustering methods measure the cost of within-cluster and between-cluster by quadratic, linear or some other unbounded functions, which may amplify the impa…
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…