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» Convergence Models of Genetic Algorithm Selection Schemes
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GECCO
2009
Springer
156views Optimization» more  GECCO 2009»
14 years 2 months ago
Characterizing the genetic programming environment for fifth (GPE5) on a high performance computing cluster
Solving complex, real-world problems with genetic programming (GP) can require extensive computing resources. However, the highly parallel nature of GP facilitates using a large n...
Kenneth Holladay
TSP
2010
13 years 2 months ago
Doubly selective channel estimation using exponential basis models and subblock tracking
Three versions of a novel adaptive channel estimation approach, exploiting the over-sampled complex exponential basis expansion model (CE-BEM), is presented fordoubly selectivechan...
Jitendra K. Tugnait, Shuangchi He, Hyosung Kim
GECCO
2010
Springer
197views Optimization» more  GECCO 2010»
14 years 13 days ago
Adaptive strategy selection in differential evolution
Differential evolution (DE) is a simple yet powerful evolutionary algorithm for global numerical optimization. Different strategies have been proposed for the offspring generation...
Wenyin Gong, Álvaro Fialho, Zhihua Cai
AAAI
2006
13 years 9 months ago
Memory Intensive Branch-and-Bound Search for Graphical Models
AND/OR search spaces have recently been introduced as a unifying paradigm for advanced algorithmic schemes for graphical models. The main virtue of this representation is its sens...
Radu Marinescu 0002, Rina Dechter
GECCO
2004
Springer
124views Optimization» more  GECCO 2004»
14 years 1 months ago
A Statistical Model of GA Dynamics for the OneMax Problem
A model of the dynamics of solving the counting-ones (OneMax) problem using a simple genetic algorithm (GA) is developed. It uses statistics of the early generations of GA runs to ...
Bulent Buyukbozkirli, Erik D. Goodman