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» Optimizing for Reduced Code Space using Genetic Algorithms
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GECCO
2007
Springer
138views Optimization» more  GECCO 2007»
15 years 8 months ago
Reducing the space-time complexity of the CMA-ES
A limited memory version of the covariance matrix adaptation evolution strategy (CMA-ES) is presented. This algorithm, L-CMA-ES, improves the space and time complexity of the CMA-...
James N. Knight, Monte Lunacek
AAAI
2000
15 years 3 months ago
Dynamic Representations and Escaping Local Optima: Improving Genetic Algorithms and Local Search
Local search algorithms often get trapped in local optima. Algorithms such as tabu search and simulated annealing 'escape' local optima by accepting nonimproving moves. ...
Laura Barbulescu, Jean-Paul Watson, L. Darrell Whi...
GECCO
2004
Springer
107views Optimization» more  GECCO 2004»
15 years 7 months ago
Multiple Species Weighted Voting - A Genetics-Based Machine Learning System
Multiple Species Weighted Voting (MSWV) is a genetics-based machine learning (GBML) system with relatively few parameters that combines N two-class classifiers into an N -class cla...
Alexander F. Tulai, Franz Oppacher
GECCO
2005
Springer
100views Optimization» more  GECCO 2005»
15 years 7 months ago
Evolutionary tree genetic programming
We introduce a clustering-based method of subpopulation management in genetic programming (GP) called Evolutionary Tree Genetic Programming (ETGP). The biological motivation behin...
Ján Antolík, William H. Hsu
IEEEPACT
2008
IEEE
15 years 8 months ago
Feature selection and policy optimization for distributed instruction placement using reinforcement learning
Communication overheads are one of the fundamental challenges in a multiprocessor system. As the number of processors on a chip increases, communication overheads and the distribu...
Katherine E. Coons, Behnam Robatmili, Matthew E. T...