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NECO
2000
190views more  NECO 2000»
14 years 9 months ago
Generalized Discriminant Analysis Using a Kernel Approach
We present a new method that we call Generalized Discriminant Analysis (GDA) to deal with nonlinear discriminant analysis using kernel function operator. The underlying theory is ...
G. Baudat, Fatiha Anouar
ACCV
2007
Springer
15 years 3 months ago
Kernel Discriminant Analysis Based on Canonical Differences for Face Recognition in Image Sets
A novel kernel discriminant transformation (KDT) algorithm based on the concept of canonical differences is presented for automatic face recognition applications. For each individu...
Wen-Sheng Vincent Chu, Ju-Chin Chen, Jenn-Jier Jam...
ICPR
2006
IEEE
15 years 10 months ago
A Convolution Edit Kernel for Error-tolerant Graph Matching
General graph matching methods often suffer from the lack of mathematical structure in the space of graphs. Using kernel functions to evaluate structural graph similarity allows u...
Horst Bunke, Michel Neuhaus
CORR
2012
Springer
171views Education» more  CORR 2012»
13 years 5 months ago
Random Feature Maps for Dot Product Kernels
Approximating non-linear kernels using feature maps has gained a lot of interest in recent years due to applications in reducing training and testing times of SVM classifiers and...
Purushottam Kar, Harish Karnick
JMLR
2008
169views more  JMLR 2008»
14 years 9 months ago
Multi-class Discriminant Kernel Learning via Convex Programming
Regularized kernel discriminant analysis (RKDA) performs linear discriminant analysis in the feature space via the kernel trick. Its performance depends on the selection of kernel...
Jieping Ye, Shuiwang Ji, Jianhui Chen