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ICTAI
2003
IEEE
13 years 10 months 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 2 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
13 years 11 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 9 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 8 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