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ALGORITHMICA
2006
74views more  ALGORITHMICA 2006»
14 years 10 months ago
Parallelizing Feature Selection
Classification is a key problem in machine learning/data mining. Algorithms for classification have the ability to predict the class of a new instance after having been trained on...
Jerffeson Teixeira de Souza, Stan Matwin, Nathalie...
CEC
2008
IEEE
15 years 4 months ago
A genetic algorithm for optimizing hierarchical menus
— Hierarchical menus are widely used as a standard user interface in modern applications that use GUIs. The performance of the menu depends on many factors: structure, layout, co...
Shouichi Matsui, Seiji Yamada
ICONIP
2004
14 years 11 months ago
Hybrid Feature Selection for Modeling Intrusion Detection Systems
Most of the current Intrusion Detection Systems (IDS) examine all data features to detect intrusion or misuse patterns. Some of the features may be redundant or contribute little (...
Srilatha Chebrolu, Ajith Abraham, Johnson P. Thoma...
GECCO
2005
Springer
232views Optimization» more  GECCO 2005»
15 years 3 months ago
A hardware pipeline for function optimization using genetic algorithms
Genetic Algorithms (GAs) are very commonly used as function optimizers, basically due to their search capability. A number of different serial and parallel versions of GA exist. ...
Malay Kumar Pakhira, Rajat K. De
EVOW
1999
Springer
15 years 2 months ago
Test Pattern Generation Under Low Power Constraints
A technique is proposed to reduce the peak power consumption of sequential circuits during test pattern application. High-speed computation intensive VLSI systems, as telecommunica...
Fulvio Corno, Maurizio Rebaudengo, Matteo Sonza Re...