356 search results - page 12 / 72 » Solving the Small Sample Size Problem of LDA |
ICPR
2008
IEEE
14 years 1 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...
CORR
2008
Springer
13 years 7 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 ...
TNN
2008
13 years 7 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 ...
SLS
2009
Springer
14 years 2 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...
ESCIENCE
2007
IEEE
13 years 11 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...