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» Gene set analysis using principal components
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ICML
2007
IEEE
14 years 9 months ago
Dimensionality reduction and generalization
In this paper we investigate the regularization property of Kernel Principal Component Analysis (KPCA), by studying its application as a preprocessing step to supervised learning ...
Sofia Mosci, Lorenzo Rosasco, Alessandro Verri
ICMCS
2005
IEEE
185views Multimedia» more  ICMCS 2005»
14 years 1 months ago
Automatic Object Trajectory-Based Motion Recognition Using Gaussian Mixture Models
In this paper, we propose a novel technique for modelbased recognition of complex object motion trajectories using Gaussian Mixture Models (GMM). We build our models on Principal ...
Faisal I. Bashir, Ashfaq A. Khokhar, Dan Schonfeld
BMCBI
2004
75views more  BMCBI 2004»
13 years 8 months ago
Joint analysis of two microarray gene-expression data sets to select lung adenocarcinoma marker genes
Background: Due to the high cost and low reproducibility of many microarray experiments, it is not surprising to find a limited number of patient samples in each study, and very f...
Hongying Jiang, Youping Deng, Huann-Sheng Chen, Li...
AIPR
2003
IEEE
14 years 1 months ago
Band Selection Using Independent Component Analysis for Hyperspectral Image Processing
Although hyperspectral images provide abundant information about objects, their high dimensionality also substantially increases computational burden. Dimensionality reduction off...
Hongtao Du, Hairong Qi, Xiaoling Wang, Rajeev Rama...
ICPR
2006
IEEE
14 years 9 months ago
Texture Segmentation Using Independent Component Analysis of Gabor Features
This paper proposes a novel method for texture segmentation using independent component analysis (ICA) of Gabor features (called ICAG). It has three distinguished aspects. (1) Gab...
Yang Chen, Runsheng Wang