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ICCV
2001
IEEE
14 years 7 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
VMV
2008
122views Visualization» more  VMV 2008»
13 years 6 months ago
Statistical analysis of Multi-Material Components using Dual Energy CT
This work describes a novel method for statistical analysis of multi-material components. The application scenario is industrial 3D X-ray computed tomography, emphasizing metrolog...
Christoph Heinzl, Johann Kastner, Torsten Möl...
ICML
2007
IEEE
14 years 6 months ago
Full regularization path for sparse principal component analysis
Given a sample covariance matrix, we examine the problem of maximizing the variance explained by a particular linear combination of the input variables while constraining the numb...
Alexandre d'Aspremont, Francis R. Bach, Laurent El...
BMCBI
2011
12 years 9 months ago
Study of large and highly stratified population datasets by combining iterative pruning principal component analysis and STRUCTU
Background: The ever increasing sizes of population genetic datasets pose great challenges for population structure analysis. The Tracy-Widom (TW) statistical test is widely used ...
Tulaya Limpiti, Apichart Intarapanich, Anunchai As...
IDEAL
2003
Springer
13 years 10 months ago
Nonlinear Multidimensional Data Projection and Visualisation
Abstract. Multidimensional data projection and visualisation are becoming increasingly important and have found wide applications in many fields such as decision support, bioinform...
Hujun Yin