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ICDM
2008
IEEE
160views Data Mining» more  ICDM 2008»
15 years 4 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
15 years 3 months 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
15 years 2 months 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
15 years 3 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»
14 years 9 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