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» Feature Subset Selection Using a Genetic Algorithm
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120
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BMCBI
2010
132views more  BMCBI 2010»
15 years 2 months ago
Error margin analysis for feature gene extraction
Background: Feature gene extraction is a fundamental issue in microarray-based biomarker discovery. It is normally treated as an optimization problem of finding the best predictiv...
Chi Kin Chow, Hai Long Zhu, Jessica Lacy, Winston ...
123
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ICCV
2007
IEEE
16 years 4 months ago
N3M: Natural 3D Markers for Real-Time Object Detection and Pose Estimation
In this paper, a new approach for object detection and pose estimation is introduced. The contribution consists in the conception of entities permitting stable detection and relia...
Stefan Hinterstoisser, Selim Benhimane, Nassir Nav...
138
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EMO
2001
Springer
150views Optimization» more  EMO 2001»
15 years 7 months ago
On the Effects of Archiving, Elitism, and Density Based Selection in Evolutionary Multi-objective Optimization
This paper studies the influence of what are recognized as key issues in evolutionary multi-objective optimization: archiving (to keep track of the current non-dominated solutions...
Marco Laumanns, Eckart Zitzler, Lothar Thiele
128
Voted
FSS
2010
147views more  FSS 2010»
15 years 1 months ago
A divide and conquer method for learning large Fuzzy Cognitive Maps
Fuzzy Cognitive Maps (FCMs) are a convenient tool for modeling and simulating dynamic systems. FCMs were applied in a large number of diverse areas and have already gained momentu...
Wojciech Stach, Lukasz A. Kurgan, Witold Pedrycz
120
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AAAI
1994
15 years 4 months ago
Evolving Neural Networks to Focus Minimax Search
Neural networks were evolved through genetic algorithms to focus minimax search in the game of Othello. At each level of the search tree, the focus networks decide which moves are...
David E. Moriarty, Risto Miikkulainen