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» Comparing evolutionary algorithms to the (1 1)-EA
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WSC
2007
13 years 7 months ago
New greedy myopic and existing asymptotic sequential selection procedures: preliminary empirical results
Statistical selection procedures can identify the best of a finite set of alternatives, where “best” is defined in terms of the unknown expected value of each alternative’...
Stephen E. Chick, Jürgen Branke, Christian Sc...
ICML
1998
IEEE
14 years 6 months ago
Q2: Memory-Based Active Learning for Optimizing Noisy Continuous Functions
This paper introduces a new algorithm, Q2, foroptimizingthe expected output ofamultiinput noisy continuous function. Q2 is designed to need only a few experiments, it avoids stron...
Andrew W. Moore, Jeff G. Schneider, Justin A. Boya...
CSB
2003
IEEE
106views Bioinformatics» more  CSB 2003»
13 years 10 months ago
Reconstruction of Ancestral Gene Order after Segmental Duplication and Gene Loss
As gene order evolves through a variety of chromosomal rearrangements, conserved segments provide important insight into evolutionary relationships and functional roles of genes. ...
Jun Huan, Jan Prins, Wei Wang 0010, Todd J. Vision
GECCO
2003
Springer
112views Optimization» more  GECCO 2003»
13 years 10 months ago
Limits in Long Path Learning with XCS
The development of the XCS Learning Classifier System [26] has produced a stable implementation, able to consistently identify the accurate and optimally general population of cla...
Alwyn Barry
BMCBI
2005
158views more  BMCBI 2005»
13 years 5 months ago
Automated generation of heuristics for biological sequence comparison
Background: Exhaustive methods of sequence alignment are accurate but slow, whereas heuristic approaches run quickly, but their complexity makes them more difficult to implement. ...
Guy St. C. Slater, Ewan Birney