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» Stability of Feature Selection Algorithms
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NIPS
2008
13 years 11 months ago
An interior-point stochastic approximation method and an L1-regularized delta rule
The stochastic approximation method is behind the solution to many important, actively-studied problems in machine learning. Despite its farreaching application, there is almost n...
Peter Carbonetto, Mark Schmidt, Nando de Freitas
PR
2006
111views more  PR 2006»
13 years 9 months ago
The Bhattacharyya space for feature selection and its application to texture segmentation
A feature selection methodology based on a novel Bhattacharyya space is presented and illustrated with a texture segmentation problem. The Bhattacharyya space is constructed from ...
Constantino Carlos Reyes-Aldasoro, Abhir Bhalerao
CVPR
2005
IEEE
14 years 11 months ago
Selection and Fusion of Color Models for Feature Detection
The choice of a color space is of great importance for many computer vision algorithms (e.g. edge detection and object recognition). It induces the equivalence classes to the actu...
Harro M. G. Stokman, Theo Gevers
CVPR
2004
IEEE
14 years 1 months ago
Face Localization via Hierarchical CONDENSATION with Fisher Boosting Feature Selection
We formulate face localization as a Maximum A Posteriori Probability(MAP) problem of finding the best estimation of human face configuration in a given image. The a prior distribu...
Jilin Tu, ZhenQiu Zhang, Zhihong Zeng, Thomas S. H...
ICIP
2010
IEEE
13 years 7 months ago
Robust object detection scheme using feature selection
Feature selection is an important issue for object detection. In this paper, we propose an effective wrapper-based feature selection scheme using Binary Particle Swarm Optimizatio...
Hong Pan, Liang-Zheng Xia, Truong Q. Nguyen