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SAC
2006
ACM
13 years 11 months ago
The impact of sample reduction on PCA-based feature extraction for supervised learning
“The curse of dimensionality” is pertinent to many learning algorithms, and it denotes the drastic raise of computational complexity and classification error in high dimension...
Mykola Pechenizkiy, Seppo Puuronen, Alexey Tsymbal
INFORMS
1998
100views more  INFORMS 1998»
13 years 5 months ago
Feature Selection via Mathematical Programming
The problem of discriminating between two nite point sets in n-dimensional feature space by a separating plane that utilizes as few of the features as possible, is formulated as a...
Paul S. Bradley, Olvi L. Mangasarian, W. Nick Stre...
ICASSP
2011
IEEE
12 years 9 months ago
SVM feature selection for multidimensional EEG data
In many machine learning applications, like Brain - Computer Interfaces (BCI), only high-dimensional noisy data are available rendering the discrimination task non-trivial. In thi...
Nisrine Jrad, Ronald Phlypo, Marco Congedo
MM
2010
ACM
402views Multimedia» more  MM 2010»
13 years 3 months ago
Discriminative codeword selection for image representation
Bag of features (BoF) representation has attracted an increasing amount of attention in large scale image processing systems. BoF representation treats images as loose collections...
Lijun Zhang 0005, Chun Chen, Jiajun Bu, Zhengguang...
ECCV
2008
Springer
14 years 7 months ago
Relevant Feature Selection for Human Pose Estimation and Localization in Cluttered Images
Abstract. We address the problem of estimating human body pose from a single image with cluttered background. We train multiple local linear regressors for estimating the 3D pose f...
Ryuzo Okada, Stefano Soatto