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» An evolutionary method for complex-process optimization
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104
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ICML
2003
IEEE
16 years 1 months ago
The Use of the Ambiguity Decomposition in Neural Network Ensemble Learning Methods
We analyze the formal grounding behind Negative Correlation (NC) Learning, an ensemble learning technique developed in the evolutionary computation literature. We show that by rem...
Gavin Brown, Jeremy L. Wyatt
GECCO
2006
Springer
205views Optimization» more  GECCO 2006»
15 years 4 months ago
Alternative evolutionary algorithms for evolving programs: evolution strategies and steady state GP
In contrast with the diverse array of genetic algorithms, the Genetic Programming (GP) paradigm is usually applied in a relatively uniform manner. Heuristics have developed over t...
L. Darrell Whitley, Marc D. Richards, J. Ross Beve...
CVPR
2012
IEEE
13 years 3 months ago
Parameter-free/Pareto-driven procedural 3D reconstruction of buildings from ground-level sequences
In this paper we address multi-view reconstruction of urban environments using 3D shape grammars. Our formulation expresses the solution to the problem as a shape grammar parse tr...
Loïc Simon, Olivier Teboul, Panagiotis Koutso...
116
Voted
GECCO
2005
Springer
127views Optimization» more  GECCO 2005»
15 years 6 months ago
The enhanced evolutionary tabu search and its application to the quadratic assignment problem
We describe the Enhanced Evolutionary Tabu Search (EE-TS) local search technique. The EE-TS metaheuristic technique combines Reactive Tabu Search with evolutionary computing eleme...
John F. McLoughlin III, Walter Cedeño
GECCO
2006
Springer
129views Optimization» more  GECCO 2006»
15 years 4 months ago
Revisiting evolutionary algorithms with on-the-fly population size adjustment
In an evolutionary algorithm, the population has a very important role as its size has direct implications regarding solution quality, speed, and reliability. Theoretical studies ...
Fernando G. Lobo, Cláudio F. Lima