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» Kernel Dimensionality Reduction for Supervised Learning
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ICML
2008
IEEE
15 years 11 months ago
A least squares formulation for canonical correlation analysis
Canonical Correlation Analysis (CCA) is a well-known technique for finding the correlations between two sets of multi-dimensional variables. It projects both sets of variables int...
Liang Sun, Shuiwang Ji, Jieping Ye
100
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CVPR
2007
IEEE
16 years 7 days ago
Biased Manifold Embedding: A Framework for Person-Independent Head Pose Estimation
The estimation of head pose angle from face images is an integral component of face recognition systems, human computer interfaces and other human-centered computing applications....
Vineeth Nallure Balasubramanian, Jieping Ye, Sethu...
KDD
2005
ACM
118views Data Mining» more  KDD 2005»
15 years 10 months ago
On the use of linear programming for unsupervised text classification
We propose a new algorithm for dimensionality reduction and unsupervised text classification. We use mixture models as underlying process of generating corpus and utilize a novel,...
Mark Sandler
CVPR
2005
IEEE
16 years 7 days ago
Discriminant Analysis with Tensor Representation
In this paper, we present a novel approach to solving the supervised dimensionality reduction problem by encoding an image object as a general tensor of 2nd or higher order. First...
Shuicheng Yan, Dong Xu, Qiang Yang, Lei Zhang, Xia...
BMCBI
2005
118views more  BMCBI 2005»
14 years 10 months ago
Feature selection and nearest centroid classification for protein mass spectrometry
Background: The use of mass spectrometry as a proteomics tool is poised to revolutionize early disease diagnosis and biomarker identification. Unfortunately, before standard super...
Ilya Levner