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110
Voted
PR
1998
86views more  PR 1998»
15 years 12 days ago
Optimizing the cost matrix for approximate string matching using genetic algorithms
This paper describes a method for optimizing the cost matrix of any approximate string matching algorithm based on the Levenshtein distance. The method, which uses genetic algorit...
Marc Parizeau, Nadia Ghazzali, Jean-Françoi...
108
Voted
ICPPW
2002
IEEE
15 years 5 months ago
Near-Optimal Loop Tiling by Means of Cache Miss Equations and Genetic Algorithms
The effectiveness of the memory hierarchy is critical for the performance of current processors. The performance of the memory hierarchy can be improved by means of program transf...
Jaume Abella, Antonio González, Josep Llosa...
ECAL
2007
Springer
15 years 7 months ago
Genotype Editing and the Evolution of Regulation and Memory
Our agent-based model of genotype editing is defined by two distinct genetic components: a coding portion encoding phenotypic solutions, and a non-coding portion used to edit the ...
Luis Mateus Rocha, Jasleen Kaur
111
Voted
CLUSTER
2008
IEEE
15 years 7 months ago
A comparison of search heuristics for empirical code optimization
—This paper describes the application of various search techniques to the problem of automatic empirical code optimization. The search process is a critical aspect of auto-tuning...
Keith Seymour, Haihang You, Jack Dongarra
109
Voted
EUROGP
2009
Springer
132views Optimization» more  EUROGP 2009»
15 years 7 months ago
A Statistical Learning Perspective of Genetic Programming
Code bloat, the excessive increase of code size, is an important issue in Genetic Programming (GP). This paper proposes a theoretical analysis of code bloat in GP from the perspec...
Nur Merve Amil, Nicolas Bredeche, Christian Gagn&e...