332 search results - page 19 / 67 » On the Performance of Chernoff-Distance-Based Linear Dimensi... |
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PR
2006
14 years 9 months ago
2006
In the past few years, some nonlinear dimensionality reduction (NLDR) or nonlinear manifold learning methods have aroused a great deal of interest in the machine learning communit...
ISQED
2008
IEEE
15 years 4 months ago
2008
IEEE
Large-scale process fluctuations (particularly random device mismatches) at nanoscale technologies bring about highdimensional strongly nonlinear performance variations that canno...
PRL
2006
14 years 9 months ago
2006
Data reduction plays an important role in machine learning and pattern recognition with a high-dimensional data. In real-world applications data usually exists with hybrid formats...
104
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PKDD
2005
Springer
15 years 3 months ago
2005
Springer
Abstract. Problem solving with experiences that are recorded in text form requires a mapping from text to structured cases, so that case comparison can provide informed feedback fo...
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TNN
2008
14 years 9 months ago
2008
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 ...