2 citations · 3 across the 3 of their papers we have counts for
7 papers
Two-dimensional Bhattacharyya bound linear discriminant analysis with its applications
Yan-Ru Guo, Yan-Qin Bai, Chun-Na Li +2
Recently proposed L2-norm linear discriminant analysis criterion via the Bhattacharyya error bound estimation (L2BLDA) is an effective improvement of linear discriminant analysis (…
Capped norm linear discriminant analysis and its applications
Jiakou Liu, Xiong Xiong, Pei-Wei Ren +3
Classical linear discriminant analysis (LDA) is based on squared Frobenious norm and hence is sensitive to outliers and noise. To improve the robustness of LDA, in this paper, we i…
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…
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…