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» Fast Independent Component Analysis in Kernel Feature Spaces
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ALT
2005
Springer
14 years 4 months ago
Measuring Statistical Dependence with Hilbert-Schmidt Norms
Abstract. We propose an independence criterion based on the eigenspectrum of covariance operators in reproducing kernel Hilbert spaces (RKHSs), consisting of an empirical estimate ...
Arthur Gretton, Olivier Bousquet, Alex J. Smola, B...
ICIP
2009
IEEE
13 years 5 months ago
An attention model for extracting components that merit identification
Cognitive systems are trained to recognise perceptually meaningful parts of an image. These regions contain some variation, i.e. local texture, and are roughly convex. We call suc...
Mohammad Jahangiri, Maria Petrou
FAST
2011
12 years 11 months ago
Making the Common Case the Only Case with Anticipatory Memory Allocation
We present Anticipatory Memory Allocation (AMA), a new method to build kernel code that is robust to memoryallocation failures. AMA avoids the usual difficulties in handling allo...
Swaminathan Sundararaman, Yupu Zhang, Sriram Subra...
ICDAR
2009
IEEE
13 years 5 months ago
Logo Detection in Document Images Based on Boundary Extension of Feature Rectangles
A new method of logo detection in document images is proposed in this paper. It is based on the boundary extension of feature rectangles of which the definition is also given in t...
Hongye Wang, Youbin Chen
PAMI
2010
192views more  PAMI 2010»
13 years 5 months ago
Multiway Spectral Clustering with Out-of-Sample Extensions through Weighted Kernel PCA
—A new formulation for multiway spectral clustering is proposed. This method corresponds to a weighted kernel principal component analysis (PCA) approach based on primal-dual lea...
Carlos Alzate, Johan A. K. Suykens