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» Unsupervised Problem Decomposition Using Genetic Programming
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ISCAS
2006
IEEE
112views Hardware» more  ISCAS 2006»
14 years 5 months ago
Towards an optimised VLSI design algorithm for the constant matrix multiplication problem
The efficient design of multiplierless implementa- The goal is to find the optimal sub-expressions across all N dot tions of constant matrix multipliers is challenged by the huge p...
Andrew Kinane, Valentin Muresan, Noel E. O'Connor
GECCO
2008
Springer
133views Optimization» more  GECCO 2008»
14 years 2 days ago
Using feature-based fitness evaluation in symbolic regression with added noise
Symbolic regression is a popular genetic programming (GP) application. Typically, the fitness function for this task is based on a sum-of-errors, involving the values of the depe...
Janine H. Imada, Brian J. Ross
CCE
2007
13 years 11 months ago
Water networks security: A two-stage mixed-integer stochastic program for sensor placement under uncertainty
This work describes a stochastic approach for the optimal placement of sensors in municipal water networks to detect maliciously injected contaminants. The model minimizes the exp...
Vicente Rico-Ramírez, Sergio Frausto-Hern&a...
IJCIA
2006
88views more  IJCIA 2006»
13 years 11 months ago
Multi-Learner Based Recursive Supervised Training
In this paper, we propose the Multi-Learner Based Recursive Supervised Training (MLRT) algorithm which uses the existing framework of recursive task decomposition, by training the...
Laxmi R. Iyer, Kiruthika Ramanathan, Sheng Uei Gua...
IPPS
2006
IEEE
14 years 5 months ago
Multiple sequence alignment by quantum genetic algorithm
In this paper we describe a new approach for the well known problem in bioinformatics: Multiple Sequence Alignment (MSA). MSA is fundamental task as it represents an essential pla...
L. Abdesslem, M. Soham, B. Mohamed