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CVPR
2007
IEEE
14 years 6 months ago
Learning a Spatially Smooth Subspace for Face Recognition
Subspace learning based face recognition methods have attracted considerable interests in recently years, including Principal Component Analysis (PCA), Linear Discriminant Analysi...
Deng Cai, Xiaofei He, Yuxiao Hu, Jiawei Han, Thoma...
WACV
2008
IEEE
13 years 11 months ago
Object Categorization Based on Kernel Principal Component Analysis of Visual Words
In recent years, many researchers are studying object categorization problem. It is reported that bag of keypoints approach which is based on local features without topological in...
Kazuhiro Hotta
MP
2010
154views more  MP 2010»
13 years 3 months ago
A null-space primal-dual interior-point algorithm for nonlinear optimization with nice convergence properties
Abstract. We present a null-space primal-dual interior-point algorithm for solving nonlinear optimization problems with general inequality and equality constraints. The algorithm a...
Xinwei Liu, Yaxiang Yuan
BMCBI
2010
243views more  BMCBI 2010»
13 years 4 months ago
Comparative study of unsupervised dimension reduction techniques for the visualization of microarray gene expression data
Background: Visualization of DNA microarray data in two or three dimensional spaces is an important exploratory analysis step in order to detect quality issues or to generate new ...
Christoph Bartenhagen, Hans-Ulrich Klein, Christia...
SDM
2009
SIAM
180views Data Mining» more  SDM 2009»
14 years 1 months ago
Hierarchical Linear Discriminant Analysis for Beamforming.
This paper demonstrates the applicability of the recently proposed supervised dimension reduction, hierarchical linear discriminant analysis (h-LDA) to a well-known spatial locali...
Barry L. Drake, Haesun Park, Jaegul Choo