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JUCS
2008
159views more  JUCS 2008»
14 years 11 months ago
Two Step Swarm Intelligence to Solve the Feature Selection Problem
: In this paper we propose a new approach to Swarm Intelligence called Two-Step Swarm Intelligence. The basic idea is to split the heuristic search performed by agents into two sta...
Yudel Gómez, Rafael Bello, Amilkar Puris, M...
TVLSI
2008
90views more  TVLSI 2008»
14 years 11 months ago
A Special-Purpose Architecture for Solving the Breakpoint Median Problem
Abstract--In this paper, we describe the design for a co-processor for whole-genome phylogenetic reconstruction. Our current design performs a parallelized breakpoint median comput...
Jason D. Bakos, Panormitis E. Elenis
GECCO
2003
Springer
15 years 4 months ago
A Kernighan-Lin Local Improvement Heuristic That Solves Some Hard Problems in Genetic Algorithms
We present a Kernighan-Lin style local improvement heuristic for genetic algorithms. We analyze the run-time cost of the heuristic. We demonstrate through experiments that the heur...
William A. Greene
GECCO
2009
Springer
199views Optimization» more  GECCO 2009»
15 years 3 months ago
Using behavioral exploration objectives to solve deceptive problems in neuro-evolution
Encouraging exploration, typically by preserving the diversity within the population, is one of the most common method to improve the behavior of evolutionary algorithms with dece...
Jean-Baptiste Mouret, Stéphane Doncieux
MOC
2000
105views more  MOC 2000»
14 years 10 months ago
On the iteratively regularized Gauss-Newton method for solving nonlinear ill-posed problems
The iteratively regularized Gauss-Newton method is applied to compute the stable solutions to nonlinear ill-posed problems F (x) = y when the data y is given approximately by y wit...
Jin Qi-nian