356 search results - page 12 / 72 » Solving the Small Sample Size Problem of LDA |
120
Voted
ICPR
2008
IEEE
15 years 8 months ago
2008
IEEE
In this paper, a novel subspace learning method, semi-supervised marginal discriminant analysis (SMDA), is proposed for classification. SMDA aims at maintaining the intrinsic neig...
140
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CORR
2008
Springer
15 years 1 months ago
2008
Springer
: Applications such as Face Recognition (FR) that deal with high-dimensional data need a mapping technique that introduces representation of low-dimensional features with enhanced ...
136
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TNN
2008
15 years 1 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 ...
115
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SLS
2009
Springer
15 years 8 months ago
2009
Springer
Stochastic local search algorithms can now successfully solve MAXSAT problems with thousands of variables or more. A key to this success is how effectively the search can navigate...
108
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ESCIENCE
2007
IEEE
15 years 5 months ago
2007
IEEE
Increasing the efficiency of meander line antennas is an important real-world problem within radio frequency identification (RFID). Meta-heuristic search algorithms, such as ant c...