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» PCA in Autocorrelation Space
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ICPR
2004
IEEE
14 years 8 months ago
Classification Probability Analysis of Principal Component Null Space Analysis
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...
Namrata Vaswani, Rama Chellappa
JMLR
2008
131views more  JMLR 2008»
13 years 7 months ago
On Relevant Dimensions in Kernel Feature Spaces
We show that the relevant information of a supervised learning problem is contained up to negligible error in a finite number of leading kernel PCA components if the kernel matche...
Mikio L. Braun, Joachim M. Buhmann, Klaus-Robert M...
TREC
2000
13 years 9 months ago
Information Space Based on HTML Structure
The main goal for the Information Space system for TREC9 was early precision. To facilitate this, an emphasis was placed on seeking matches from only the TITLE, H1, H2 and H3 tags...
Gregory B. Newby
ICIP
1999
IEEE
14 years 9 months ago
Hypercomplex Auto-And-Cross-Correlation of Color Images
Autocorrelation and cross-correlation have been defined and utilized in signal and image processing for many years, but not for color or vector images. In this poster we present f...
Stephen J. Sangwine, Todd A. Ell
JMLR
2006
105views more  JMLR 2006»
13 years 7 months ago
Linear State-Space Models for Blind Source Separation
We apply a type of generative modelling to the problem of blind source separation in which prior knowledge about the latent source signals, such as time-varying auto-correlation a...
Rasmus Kongsgaard Olsson, Lars Kai Hansen