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JMLR
2010
182views more  JMLR 2010»
12 years 11 months ago
Quadratic Programming Feature Selection
Identifying a subset of features that preserves classification accuracy is a problem of growing importance, because of the increasing size and dimensionality of real-world data se...
Irene Rodriguez-Lujan, Ramón Huerta, Charle...
KDD
2007
ACM
197views Data Mining» more  KDD 2007»
14 years 5 months ago
Learning the kernel matrix in discriminant analysis via quadratically constrained quadratic programming
The kernel function plays a central role in kernel methods. In this paper, we consider the automated learning of the kernel matrix over a convex combination of pre-specified kerne...
Jieping Ye, Shuiwang Ji, Jianhui Chen

Publication
433views
14 years 1 months ago
Optimal Feature Selection for Subspace Image Matching
Image matching has been a central research topic in computer vision over the last decades. Typical approaches for correspondence involve matching features between images. In this p...
Gemma Roig, Xavier Boix, Fernando De la Torre

Publication
210views
14 years 1 days ago
Optimal Feature Selection for Subspace Image Matching
Image matching has been a central research topic in computer vision over the last decades. Typical approaches to correspondence involve matching features between images. In this pa...
Gemma Roig, Xavier Boix, Fernando De la Torre
ICML
2004
IEEE
13 years 10 months ago
Gradient LASSO for feature selection
LASSO (Least Absolute Shrinkage and Selection Operator) is a useful tool to achieve the shrinkage and variable selection simultaneously. Since LASSO uses the L1 penalty, the optim...
Yongdai Kim, Jinseog Kim