441 search results - page 19 / 89 » Linear Discriminant Analysis for Signatures |
146
Voted
KAIS
2006
15 years 3 months ago
2006
Abstract. Many supervised machine learning tasks can be cast as multi-class classification problems. Support vector machines (SVMs) excel at binary classification problems, but the...
144
Voted
PAMI
2011
14 years 10 months ago
2011
— Kernel mapping is one of the most used approaches to intrinsically derive nonlinear classifiers. The idea is to use a kernel function which maps the original nonlinearly separ...
138
Voted
ICPR
2008
IEEE
16 years 4 months ago
2008
IEEE
Speaker independent feature extraction is a critical problem in speech recognition. Oriented principal component analysis (OPCA) is a potential solution that can find a subspace r...
144
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CVPR
2010
IEEE
15 years 7 months ago
2010
IEEE
Kernel methods provide an efficient mechanism to derive nonlinear algorithms. In classification problems as well as in feature extraction, kernel-based approaches map the original...
134
Voted
JMLR
2010
14 years 10 months ago
2010
Fisher linear discriminant analysis (FDA) and its kernel extension--kernel discriminant analysis (KDA)--are well known methods that consider dimensionality reduction and classific...