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SIAMMAX
2010
189views more  SIAMMAX 2010»
9 years 8 months ago
Fast Algorithms for the Generalized Foley-Sammon Discriminant Analysis
Linear Discriminant Analysis (LDA) is one of the most popular approaches for feature extraction and dimension reduction to overcome the curse of the dimensionality of the high-dime...
Lei-Hong Zhang, Li-Zhi Liao, Michael K. Ng
TNN
2010
149views Management» more  TNN 2010»
9 years 8 months ago
A rank-one update algorithm for fast solving kernel Foley-Sammon optimal discriminant vectors
Discriminant analysis plays an important role in statistical pattern recognition. A popular method is the Foley
Wenming Zheng, Zhouchen Lin, Xiaoou Tang
PR
2008
129views more  PR 2008»
10 years 1 months ago
A comparison of generalized linear discriminant analysis algorithms
7 Linear discriminant analysis (LDA) is a dimension reduction method which finds an optimal linear transformation that maximizes the class separability. However, in undersampled p...
Cheong Hee Park, Haesun Park
CVPR
2008
IEEE
11 years 3 months ago
A unified framework for generalized Linear Discriminant Analysis
Linear Discriminant Analysis (LDA) is one of the wellknown methods for supervised dimensionality reduction. Over the years, many LDA-based algorithms have been developed to cope w...
Shuiwang Ji, Jieping Ye
TNN
2008
105views more  TNN 2008»
10 years 1 months ago
Generalized Linear Discriminant Analysis: A Unified Framework and Efficient Model Selection
Abstract--High-dimensional data are common in many domains, and dimensionality reduction is the key to cope with the curse-of-dimensionality. Linear discriminant analysis (LDA) is ...
Shuiwang Ji, Jieping Ye
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