119 search results - page 2 / 24 » Constrained Projection Approximation Algorithms for Principa... |
CSDA
2004
13 years 5 months ago
2004
Variable selection consists in identifying a k-subset of a set of original variables that is optimal for a given criterion of adequate approximation to the whole data set. Several...
TIFS
2008
13 years 5 months ago
2008
We present a theory for constructing linear subspace approximations to face-recognition algorithms and empirically demonstrate that a surprisingly diverse set of face-recognition a...
ICPR
2004
IEEE
14 years 6 months ago
2004
IEEE
In a previous paper [1], we have presented a new linear classification algorithm, Principal Component Null Space Analysis (PCNSA) which is designed for problems like object recogn...
ICONIP
2007
13 years 6 months ago
2007
Abstract. Principal component analysis (PCA) is a widely used technique for data analysis and dimensionality reduction. Eigenvalue decomposition is the standard algorithm for solvi...
ICIP
2008
IEEE
14 years 7 months ago
2008
IEEE
This paper presents an image denoising algorithm that uses principal component analysis (PCA) in conjunction with the non-local means image denoising. Image neighborhood vectors u...