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» Dimensionality Reduction for Classification
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IJCAI
2007
15 years 4 months ago
A Subspace Kernel for Nonlinear Feature Extraction
Kernel based nonlinear Feature Extraction (KFE) or dimensionality reduction is a widely used pre-processing step in pattern classification and data mining tasks. Given a positive...
Mingrui Wu, Jason D. R. Farquhar
NPL
1998
135views more  NPL 1998»
15 years 2 months ago
Local Adaptive Subspace Regression
Abstract. Incremental learning of sensorimotor transformations in high dimensional spaces is one of the basic prerequisites for the success of autonomous robot devices as well as b...
Sethu Vijayakumar, Stefan Schaal
CVPR
2007
IEEE
16 years 5 months ago
Segmenting Motions of Different Types by Unsupervised Manifold Clustering
We propose a novel algorithm for segmenting multiple motions of different types from point correspondences in multiple affine or perspective views. Since point trajectories associ...
Alvina Goh, René Vidal
BMCBI
2008
147views more  BMCBI 2008»
15 years 3 months ago
Simple integrative preprocessing preserves what is shared in data sources
Background: Bioinformatics data analysis toolbox needs general-purpose, fast and easily interpretable preprocessing tools that perform data integration during exploratory data ana...
Abhishek Tripathi, Arto Klami, Samuel Kaski
BMCBI
2008
160views more  BMCBI 2008»
15 years 3 months ago
Feature selection environment for genomic applications
Background: Feature selection is a pattern recognition approach to choose important variables according to some criteria in order to distinguish or explain certain phenomena (i.e....
Fabrício Martins Lopes, David Correa Martin...