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ICDM
2003
IEEE
153views Data Mining» more  ICDM 2003»
14 years 19 days 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
CIKM
2008
Springer
13 years 9 months ago
REDUS: finding reducible subspaces in high dimensional data
Finding latent patterns in high dimensional data is an important research problem with numerous applications. The most well known approaches for high dimensional data analysis are...
Xiang Zhang, Feng Pan, Wei Wang 0010
ICIP
2005
IEEE
14 years 9 months 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
ICCV
2003
IEEE
14 years 9 months ago
Weighted and Robust Incremental Method for Subspace Learning
Visual learning is expected to be a continuous and robust process, which treats input images and pixels selectively. In this paper we present a method for subspace learning, which...
Danijel Skocaj, Ales Leonardis
CVPR
1999
IEEE
14 years 9 months ago
Simultaneous Extraction of Functional Face Subspaces
Facial variation divides into a number of functional subspaces. An improved method of measuring these was designed, within the space defined by an Appearance Model. Initial estima...
Nicholas Costen, Timothy F. Cootes, Gareth J. Edwa...