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ICDM
2008
IEEE
160views Data Mining» more  ICDM 2008»
14 years 1 months ago
Direct Zero-Norm Optimization for Feature Selection
Zero-norm, defined as the number of non-zero elements in a vector, is an ideal quantity for feature selection. However, minimization of zero-norm is generally regarded as a combi...
Kaizhu Huang, Irwin King, Michael R. Lyu
ICNC
2005
Springer
14 years 26 days ago
Training Data Selection for Support Vector Machines
Abstract. In recent years, support vector machines (SVMs) have become a popular tool for pattern recognition and machine learning. Training a SVM involves solving a constrained qua...
Jigang Wang, Predrag Neskovic, Leon N. Cooper
CGO
2003
IEEE
14 years 20 days ago
Addressing Mode Selection
Many processor architectures provide a set of addressing modes in their address generation units. For example DSPs (digital signal processors) have powerful addressing modes for e...
Erik Eckstein, Bernhard Scholz
IJCNN
2008
IEEE
14 years 1 months ago
Sparse kernel density estimator using orthogonal regression based on D-Optimality experimental design
— A novel sparse kernel density estimator is derived based on a regression approach, which selects a very small subset of significant kernels by means of the D-optimality experi...
Sheng Chen, Xia Hong, Chris J. Harris
COR
2007
134views more  COR 2007»
13 years 7 months ago
Portfolio selection using neural networks
In this paper we apply a heuristic method based on artificial neural networks (NN) in order to trace out the efficient frontier associated to the portfolio selection problem. We...
Alberto Fernández, Sergio Gómez