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» Generalized Discriminant Analysis Using a Kernel Approach
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CVPR
2001
IEEE
14 years 9 months ago
Small Sample Learning during Multimedia Retrieval using BiasMap
All positive examples are alike; each negative example is negative in its own way. During interactive multimedia information retrieval, the number of training samples fed-back by ...
Xiang Sean Zhou, Thomas S. Huang
VISUAL
2005
Springer
14 years 1 months ago
Face Recognition Using Modular Bilinear Discriminant Analysis
We present a Modular Bilinear Disciminant Analysis (MBDA) approach for face recognition. A set of classifiers are trained independently on specific face regions, and different c...
Muriel Visani, Christophe Garcia, Jean-Michel Joli...
AVBPA
2005
Springer
226views Biometrics» more  AVBPA 2005»
14 years 1 months ago
Discriminant Analysis Based on Kernelized Decision Boundary for Face Recognition
A novel nonlinear discriminant analysis method, Kernelized Decision Boundary Analysis (KDBA), is proposed in our paper, whose Decision Boundary feature vectors are the normal vecto...
Baochang Zhang, Xilin Chen, Wen Gao
SMI
2010
IEEE
165views Image Analysis» more  SMI 2010»
13 years 5 months ago
Designing a Topological Modeler Kernel: A Rule-Based Approach
In this article, we present a rule-based language dedicated to topological operations, based on graph transformations. Generalized maps are described as a particular class of graph...
Thomas Bellet, Mathieu Poudret, Agnès Arnou...
ICDM
2009
IEEE
174views Data Mining» more  ICDM 2009»
14 years 2 months ago
Non-sparse Multiple Kernel Learning for Fisher Discriminant Analysis
—We consider the problem of learning a linear combination of pre-specified kernel matrices in the Fisher discriminant analysis setting. Existing methods for such a task impose a...
Fei Yan, Josef Kittler, Krystian Mikolajczyk, Muha...