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ICMLA
2008

An Improved Generalized Discriminant Analysis for Large-Scale Data Set

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An Improved Generalized Discriminant Analysis for Large-Scale Data Set
In order to overcome the computation and storage problem for large-scale data set, an efficient iterative method of Generalized Discriminant Analysis is proposed. Because sample vectors cannot explicitly be denoted in kernel space, some mathematical tricks are firstly used to transform the kernel matrix. Then, the columns of transformed matrix are used for iterative algorithm to extract nonlinear discriminant vectors. The proposed method reduces space complexity from o(m2 ) to o(m) and its effectiveness is validated from experimental results.
Weiya Shi, Yue-Fei Guo, Cheng Jin, Xiangyang Xue
Added 29 Oct 2010
Updated 29 Oct 2010
Type Conference
Year 2008
Where ICMLA
Authors Weiya Shi, Yue-Fei Guo, Cheng Jin, Xiangyang Xue
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