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SDM
2008
SIAM
117views Data Mining» more  SDM 2008»
14 years 11 months ago
A Feature Selection Algorithm Capable of Handling Extremely Large Data Dimensionality
With the advent of high throughput technologies, feature selection has become increasingly important in a wide range of scientific disciplines. We propose a new feature selection ...
Yijun Sun, Sinisa Todorovic, Steve Goodison
SCIA
2009
Springer
140views Image Analysis» more  SCIA 2009»
15 years 4 months ago
Fast Prototype Based Noise Reduction
This paper introduces a novel method for noise reduction in medical images based on concepts of the Non-Local Means algorithm. The main objective has been to develop a method that ...
Kajsa Tibell, Hagen Spies, Magnus Borga
CVPR
2008
IEEE
15 years 12 months ago
A unified framework for generalized Linear Discriminant Analysis
Linear Discriminant Analysis (LDA) is one of the wellknown methods for supervised dimensionality reduction. Over the years, many LDA-based algorithms have been developed to cope w...
Shuiwang Ji, Jieping Ye
IJCV
2008
155views more  IJCV 2008»
14 years 10 months ago
Fast Transformation-Invariant Component Analysis
For software and more illustrations: http://www.psi.utoronto.ca/anitha/fastTCA.htm Dimensionality reduction techniques such as principal component analysis and factor analysis are...
Anitha Kannan, Nebojsa Jojic, Brendan J. Frey
CAIP
1997
Springer
125views Image Analysis» more  CAIP 1997»
15 years 1 months ago
An Algorithm for Intrinsic Dimensionality Estimation
Abstract. In this paper a new method for analyzing the intrinsic dimensionality (ID) of low dimensional manifolds in high dimensional feature spaces is presented. The basic idea is...
Jörg Bruske, Gerald Sommer