288 search results - page 25 / 58 » A New Approach to Multi-class Linear Dimensionality Reductio... |
135
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ECCV
2006
Springer
16 years 3 months ago
2006
Springer
Many linear discriminant analysis (LDA) and kernel Fisher discriminant analysis (KFD) methods are based on the restrictive assumption that the data are homoscedastic. In this paper...
135
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ICALP
2007
Springer
15 years 8 months ago
2007
Springer
Abstract. We develop a generic framework for deriving linear-size problem kernels for NP-hard problems on planar graphs. We demonstrate the usefulness of our framework in several c...
121
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TVLSI
2010
14 years 8 months ago
2010
In many applications, a reduction of the amount of the original data or a representation of the original data by a small set of variables is often required. Among many techniques, ...
101
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ICDM
2009
IEEE
15 years 8 months ago
2009
IEEE
Abstract—Linear discriminant analysis (LDA) is a wellknown dimension reduction approach, which projects highdimensional data into a low-dimensional space with the best separation...
121
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ICASSP
2010
IEEE
15 years 2 months ago
2010
IEEE
The problem of minimizing the rank of a matrix subject to linear equality constraints arises in applications in machine learning, dimensionality reduction, and control theory, and...