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ICTAI
2003
IEEE
14 years 12 days ago
Engineering Optimization Using a Simple Evolutionary Algorithm
This paper presents a simple ¢¤£¦¥¨§© Evolution Strategy and three simple selection criteria to solve engineering optimization problems. This approach avoids the use of a...
Efrén Mezura-Montes, Carlos A. Coello Coell...
GECCO
2009
Springer
162views Optimization» more  GECCO 2009»
13 years 4 months ago
Uncertainty handling CMA-ES for reinforcement learning
The covariance matrix adaptation evolution strategy (CMAES) has proven to be a powerful method for reinforcement learning (RL). Recently, the CMA-ES has been augmented with an ada...
Verena Heidrich-Meisner, Christian Igel
ICASSP
2008
IEEE
14 years 1 months ago
Belief propagation distributed estimation in sensor networks: An optimized energy accuracy tradeoff
The estimation error performance of Gaussian belief propagation based distributed estimation in a large sensor network employing random sleep strategies is explicitly evaluated fo...
John MacLaren Walsh, Phillip A. Regalia
GECCO
2010
Springer
193views Optimization» more  GECCO 2010»
13 years 12 months ago
Fitness-AUC bandit adaptive strategy selection vs. the probability matching one within differential evolution: an empirical comp
The choice of which of the available strategies should be used within the Differential Evolution algorithm for a given problem is not trivial, besides being problem-dependent and...
Álvaro Fialho, Marc Schoenauer, Michè...
ICASSP
2011
IEEE
12 years 10 months ago
Generalized low-rank decompositions with switching and adaptive algorithms for space-time adaptive processing
This work presents generalized low-rank signal decompositions with the aid of switching techniques and adaptive algorithms, which do not require eigen-decompositions, for space-ti...
Rodrigo C. de Lamare