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» Stahel-Donoho estimation for high-dimensional data
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PKDD
2009
Springer
148views Data Mining» more  PKDD 2009»
16 years 28 days ago
Feature Selection by Transfer Learning with Linear Regularized Models
Abstract. This paper presents a novel feature selection method for classification of high dimensional data, such as those produced by microarrays. It includes a partial supervisio...
Thibault Helleputte, Pierre Dupont
ICPR
2006
IEEE
16 years 7 months ago
Segmentation and Probabilistic Registration of Articulated Body Models
There are different approaches to pose estimation and registration of different body parts using voxel data. We propose a general bottom-up approach in order to segment the voxels...
Aravind Sundaresan, Rama Chellappa
BMCBI
2010
113views more  BMCBI 2010»
15 years 6 months ago
Probabilistic Principal Component Analysis for Metabolomic Data
Background: Data from metabolomic studies are typically complex and high-dimensional. Principal component analysis (PCA) is currently the most widely used statistical technique fo...
Gift Nyamundanda, Lorraine Brennan, Isobel Claire ...
ICCV
2001
IEEE
16 years 8 months ago
Robust Principal Component Analysis for Computer Vision
Principal Component Analysis (PCA) has been widely used for the representation of shape, appearance, and motion. One drawback of typical PCA methods is that they are least squares...
Fernando De la Torre, Michael J. Black
ICASSP
2007
IEEE
16 years 21 days ago
Feature Selection Based on Fisher Ratio and Mutual Information Analyses for Robust Brain Computer Interface
This paper proposes a novel feature selection method based on twostage analysis of Fisher Ratio and Mutual Information for robust Brain Computer Interface. This method decomposes ...
Tran Huy Dat, Cuntai Guan