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» Laplacian PCA and Its Applications
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FGR
2006
IEEE
169views Biometrics» more  FGR 2006»
14 years 6 days ago
Combining PCA and LFA for Surface Reconstruction from a Sparse Set of Control Points
This paper presents a novel method for 3D surface reconstruction based on a sparse set of 3D control points. For object classes such as human heads, prior information about the cl...
Reinhard Knothe, Sami Romdhani, Thomas Vetter
ICPR
2010
IEEE
13 years 8 months ago
Temporal Extension of Laplacian Eigenmaps for Unsupervised Dimensionality Reduction of Time Series
—A novel non-linear dimensionality reduction method, called Temporal Laplacian Eigenmaps, is introduced to process efficiently time series data. In this embedded-based approach,...
Michal Lewandowski, Jesus Martinez-Del-Rincon, Dim...
NIPS
2004
13 years 7 months ago
A Direct Formulation for Sparse PCA Using Semidefinite Programming
We examine the problem of approximating, in the Frobenius-norm sense, a positive, semidefinite symmetric matrix by a rank-one matrix, with an upper bound on the cardinality of its...
Alexandre d'Aspremont, Laurent El Ghaoui, Michael ...
ICML
2008
IEEE
14 years 7 months ago
Expectation-maximization for sparse and non-negative PCA
We study the problem of finding the dominant eigenvector of the sample covariance matrix, under additional constraints on the vector: a cardinality constraint limits the number of...
Christian D. Sigg, Joachim M. Buhmann
ICIP
2009
IEEE
13 years 3 months ago
PCA Gaussianization for image processing
The estimation of high-dimensional probability density functions (PDFs) is not an easy task for many image processing applications. The linear models assumed by widely used transf...
Valero Laparra, Gustavo Camps-Valls, Jesús ...