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GECCO
2010
Springer
244views Optimization» more  GECCO 2010»
13 years 5 months ago
Implicit fitness and heterogeneous preferences in the genetic algorithm
This paper takes an economic approach to derive an evolutionary learning model based entirely on the endogenous employment of genetic operators in the service of self-interested a...
Justin T. H. Smith
GPEM
2008
98views more  GPEM 2008»
13 years 5 months ago
Sporadic model building for efficiency enhancement of the hierarchical BOA
Efficiency enhancement techniques--such as parallelization and hybridization--are among the most important ingredients of practical applications of genetic and evolutionary algori...
Martin Pelikan, Kumara Sastry, David E. Goldberg
BMCBI
2005
106views more  BMCBI 2005»
13 years 5 months ago
SIMPROT: Using an empirically determined indel distribution in simulations of protein evolution
Background: General protein evolution models help determine the baseline expectations for the evolution of sequences, and they have been extensively useful in sequence analysis an...
Andy Pang, Andrew D. Smith, Paulo A. S. Nuin, Elis...
EOR
2007
100views more  EOR 2007»
13 years 5 months ago
Parallel radial basis function methods for the global optimization of expensive functions
We introduce a master–worker framework for parallel global optimization of computationally expensive functions using response surface models. In particular, we parallelize two r...
Rommel G. Regis, Christine A. Shoemaker
CVPR
2006
IEEE
14 years 7 months ago
Object Pose Detection in Range Scan Data
We address the problem of detecting complex articulated objects and their pose in 3D range scan data. This task is very difficult when the orientation of the object is unknown, an...
Jim Rodgers, Dragomir Anguelov, Hoi-Cheung Pang, D...