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» Two-Dimensional Linear Discriminant Analysis
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ICML
2005
IEEE
14 years 8 months ago
Building Sparse Large Margin Classifiers
This paper presents an approach to build Sparse Large Margin Classifiers (SLMC) by adding one more constraint to the standard Support Vector Machine (SVM) training problem. The ad...
Bernhard Schölkopf, Gökhan H. Bakir, Min...
ISBI
2004
IEEE
14 years 8 months ago
Nonlinear Dimension Reduction of fMRI Data: The Laplacian Embedding Approach
In this paper, we introduce the use of nonlinear dimension reduction for the analysis of functional neuroimaging datasets. Using a Laplacian Embedding approach, we show the power ...
Olivier D. Faugeras, Bertrand Thirion
ICASSP
2008
IEEE
14 years 2 months ago
An empirical study of automatic accent classification
This paper extends language identification (LID) techniques to a large scale accent classification task: 23-way classification of foreign-accented English. We find that a pure...
Ghinwa F. Choueiter, Geoffrey Zweig, Patrick Nguye...
IJCNN
2008
IEEE
14 years 1 months ago
Learning adaptive subject-independent P300 models for EEG-based brain-computer interfaces
Abstract— This paper proposes an approach to learn subjectindependent P300 models for EEG-based brain-computer interfaces. The P300 models are first learned using a pool of exis...
Shijian Lu, Cuntai Guan, Haihong Zhang
ICPR
2006
IEEE
14 years 1 months ago
Face Recognition Using Angular LDA and SVM Ensembles
One successful approach to feature extraction in face recognition problems is that of linear discriminant analysis (LDA). We examine an extension of this technique, called angular...
Raymond S. Smith, Josef Kittler, Miroslav Hamouz, ...