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» Using Machine Learning to Focus Iterative Optimization
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GECCO
2004
Springer
125views Optimization» more  GECCO 2004»
15 years 7 months ago
Population-Based Iterated Local Search: Restricting Neighborhood Search by Crossover
Abstract. Iterated local search (ILS) is a powerful meta-heuristic algorithm applied to a large variety of combinatorial optimization problems. Contrary to evolutionary algorithms ...
Dirk Thierens
120
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GECCO
2008
Springer
123views Optimization» more  GECCO 2008»
15 years 3 months ago
Hierarchical evolution of linear regressors
We propose an algorithm for function approximation that evolves a set of hierarchical piece-wise linear regressors. The algorithm, named HIRE-Lin, follows the iterative rule learn...
Francesc Teixidó-Navarro, Albert Orriols-Pu...
ICSM
2006
IEEE
15 years 8 months ago
Using the Case-Based Ranking Methodology for Test Case Prioritization
The test case execution order affects the time at which the objectives of testing are met. If the objective is fault detection, an inappropriate execution order might reveal most ...
Paolo Tonella, Paolo Avesani, Angelo Susi
ICAI
2004
15 years 3 months ago
Task Oriented Machine-Learning and Review
We propose an optimization algorithm to execute a previously unlearned task-oriented command in an intelligent machine. We show that a well-defined, physically bounded, task-orien...
Pierre Abdelmalek, Howard E. Michel
ECML
2006
Springer
15 years 6 months ago
An Adaptive Kernel Method for Semi-supervised Clustering
Semi-supervised clustering uses the limited background knowledge to aid unsupervised clustering algorithms. Recently, a kernel method for semi-supervised clustering has been introd...
Bojun Yan, Carlotta Domeniconi