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ICIP
2005
IEEE
15 years 19 days ago
Nonlinear dimensionality reduction for classification using kernel weighted subspace method
We study the use of kernel subspace methods that learn low-dimensional subspace representations for classification tasks. In particular, we propose a new method called kernel weigh...
Guang Dai, Dit-Yan Yeung
ICDM
2003
IEEE
153views Data Mining» more  ICDM 2003»
14 years 4 months ago
Dimensionality Reduction Using Kernel Pooled Local Discriminant Information
We study the use of kernel subspace methods for learning low-dimensional representations for classification. We propose a kernel pooled local discriminant subspace method and com...
Peng Zhang, Jing Peng, Carlotta Domeniconi
ICANN
2001
Springer
14 years 3 months ago
Sparse Kernel Regressors
Sparse kernel regressors have become popular by applying the support vector method to regression problems. Although this approach has been shown to exhibit excellent generalization...
Volker Roth
CORR
2012
Springer
171views Education» more  CORR 2012»
12 years 6 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
IADIS
2004
14 years 11 days ago
Group-Oriented Learning and Active Student Participation in Electronic Learning Environments
The e-learning project GOLEM introduces a group and role-oriented concept to the course "Man-Machine Interfaces" at the University of Technology in Hamburg, Germany. Stu...
Martin Vogel, Lothar Kreft