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CORR
2012
Springer
225views Education» more  CORR 2012»
12 years 6 months ago
Compressive Principal Component Pursuit
We consider the problem of recovering a target matrix that is a superposition of low-rank and sparse components, from a small set of linear measurements. This problem arises in co...
John Wright, Arvind Ganesh, Kerui Min, Yi Ma
CVPR
2007
IEEE
15 years 11 days ago
Learning Object Material Categories via Pairwise Discriminant Analysis
In this paper, we investigate linear discriminant analysis (LDA) methods for multiclass classification problems in hyperspectral imaging. We note that LDA does not consider pairwi...
Zhouyu Fu, Antonio Robles-Kelly
ICFCA
2009
Springer
14 years 5 months ago
Factor Analysis of Incidence Data via Novel Decomposition of Matrices
Matrix decomposition methods provide representations of an object-variable data matrix by a product of two different matrices, one describing relationship between objects and hidd...
Radim Belohlávek, Vilém Vychodil
TIP
2011
162views more  TIP 2011»
13 years 5 months ago
Kernel Maximum Autocorrelation Factor and Minimum Noise Fraction Transformations
—This paper introduces kernel versions of maximum autocorrelation factor (MAF) analysis and minimum noise fraction (MNF) analysis. The kernel versions are based upon a dual formu...
Allan Aasbjerg Nielsen
SCALESPACE
2001
Springer
14 years 2 months ago
Down-Scaling for Better Transform Compression
Abstract. The most popular lossy image compression method used on the Internet is the JPEG standard. JPEG’s good compression performance and low computational and memory complexi...
Alfred M. Bruckstein, Michael Elad, Ron Kimmel