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JMLR
2010
143views more  JMLR 2010»
13 years 2 months ago
Regularized Discriminant Analysis, Ridge Regression and Beyond
Fisher linear discriminant analysis (FDA) and its kernel extension--kernel discriminant analysis (KDA)--are well known methods that consider dimensionality reduction and classific...
Zhihua Zhang, Guang Dai, Congfu Xu, Michael I. Jor...
PAMI
2011
13 years 2 months ago
Kernel Optimization in Discriminant Analysis
— 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...
Di You, Onur C. Hamsici, Aleix M. Martínez
JMLR
2008
169views more  JMLR 2008»
13 years 7 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
SDM
2008
SIAM
118views Data Mining» more  SDM 2008»
13 years 8 months ago
Massive-Scale Kernel Discriminant Analysis: Mining for Quasars
We describe a fast algorithm for kernel discriminant analysis, empirically demonstrating asymptotic speed-up over the previous best approach. We achieve this with a new pattern of...
Ryan Riegel, Alexander Gray, Gordon Richards
ICANN
2007
Springer
13 years 11 months ago
Fuzzy Classifiers Based on Kernel Discriminant Analysis
In this paper, we discuss fuzzy classifiers based on Kernel Discriminant Analysis (KDA) for two-class problems. In our method, first we employ KDA to the given training data and ca...
Ryota Hosokawa, Shigeo Abe
KDD
2007
ACM
197views Data Mining» more  KDD 2007»
14 years 7 months ago
Learning the kernel matrix in discriminant analysis via quadratically constrained quadratic programming
The kernel function plays a central role in kernel methods. In this paper, we consider the automated learning of the kernel matrix over a convex combination of pre-specified kerne...
Jieping Ye, Shuiwang Ji, Jianhui Chen
CVPR
2006
IEEE
14 years 9 months ago
Kernel Uncorrelated and Orthogonal Discriminant Analysis: A Unified Approach
Several kernel algorithms have recently been proposed for nonlinear discriminant analysis. However, these methods mainly address the singularity problem in the high dimensional fe...
Tao Xiong, Jieping Ye, Vladimir Cherkassky
CVPR
2005
IEEE
14 years 9 months ago
Coupled Kernel-Based Subspace Learning
It was prescriptive that an image matrix was transformed into a vector before the kernel-based subspace learning. In this paper, we take the Kernel Discriminant Analysis (KDA) alg...
Shuicheng Yan, Dong Xu, Lei Zhang, Benyu Zhang, Ho...
CVPR
2001
IEEE
14 years 9 months ago
Constructing Facial Identity Surfaces in a Nonlinear Discriminating Space
Recognising face with large pose variation is more challenging than that in a fixed view, e.g. frontal-view, due to the severe non-linearity caused by rotation in depth, selfshadi...
Yongmin Li, Shaogang Gong, Heather M. Liddell