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» Gene set analysis using principal components
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CVPR
2005
IEEE
14 years 10 months ago
Online Detection and Classification of Moving Objects Using Progressively Improving Detectors
Boosting based detection methods have successfully been used for robust detection of faces and pedestrians. However, a very large amount of labeled examples are required for train...
Omar Javed, Saad Ali, Mubarak Shah
MVA
2002
116views Computer Vision» more  MVA 2002»
13 years 7 months ago
Contour Extraction in Medical Images Using B-Snake Model
In this paper, a close-form B-snake model is presented for contour extraction in medical images. Based on our previous research work [lo], the Principal Component Analysis (PCA) h...
Yue Wang, Eam Khwang Teoh
NECO
1998
151views more  NECO 1998»
13 years 7 months ago
Nonlinear Component Analysis as a Kernel Eigenvalue Problem
We describe a new method for performing a nonlinear form of Principal Component Analysis. By the use of integral operator kernel functions, we can e ciently compute principal comp...
Bernhard Schölkopf, Alex J. Smola, Klaus-Robe...
BMCBI
2006
119views more  BMCBI 2006»
13 years 8 months ago
Utilization of two sample t-test statistics from redundant probe sets to evaluate different probe set algorithms in GeneChip stu
Background: The choice of probe set algorithms for expression summary in a GeneChip study has a great impact on subsequent gene expression data analysis. Spiked-in cRNAs with know...
Zihua Hu, Gail R. Willsky
NIPS
2000
13 years 9 months ago
Automatic Choice of Dimensionality for PCA
A central issue in principal component analysis (PCA) is choosing the number of principal components to be retained. By interpreting PCA as density estimation, this paper shows ho...
Thomas P. Minka