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CVPR
2009
IEEE
15 years 4 months ago
Symmetric two dimensional linear discriminant analysis (2DLDA)
Linear discriminant analysis (LDA) has been successfully applied into computer vision and pattern recognition for effective feature extraction. High-dimensional objects such as im...
Dijun Luo, Chris H. Q. Ding, Heng Huang
ACML
2009
Springer
15 years 4 months ago
Robust Discriminant Analysis Based on Nonparametric Maximum Entropy
In this paper, we propose a Robust Discriminant Analysis based on maximum entropy (MaxEnt) criterion (MaxEnt-RDA), which is derived from a nonparametric estimate of Renyi’s quadr...
Ran He, Bao-Gang Hu, Xiaotong Yuan
SDM
2008
SIAM
118views Data Mining» more  SDM 2008»
14 years 11 months ago
Massive-Scale Kernel Discriminant Analysis: Mining for Quasars
We describe a fast algorithm for kernel discriminant analysis, empirically demonstrating asymptotic speed-up over the previous best approach. We achieve this with a new pattern of...
Ryan Riegel, Alexander Gray, Gordon Richards
ICPR
2008
IEEE
15 years 11 months ago
Multiclass spectral clustering based on discriminant analysis
Many existing spectral clustering algorithms share a conventional graph partitioning criterion: normalized cuts (NC). However, one problem with NC is that it poorly captures the g...
Xi Li, Zhongfei Zhang, Yanguo Wang, Weiming Hu
ICPR
2006
IEEE
15 years 11 months ago
Non-Iterative Two-Dimensional Linear Discriminant Analysis
Linear discriminant analysis (LDA) is a well-known scheme for feature extraction and dimensionality reduction of labeled data in a vector space. Recently, LDA has been extended to...
Kohei Inoue, Kiichi Urahama