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GECCO
2006
Springer
178views Optimization» more  GECCO 2006»
15 years 5 months ago
Adaptively choosing niching parameters in a PSO
Niching techniques play an important role in evolutionary algorithms. Existing niching methods often require userspecified parameters, limiting their usefulness. This paper propos...
Stefan Bird, Xiaodong Li
GECCO
2008
Springer
170views Optimization» more  GECCO 2008»
15 years 2 months ago
Evolving prediction weights using evolution strategy
The evolution strategy is one of the strongest evolutionary algorithms for optimizing real-value vectors. In this paper, we study how to use it for the evolution of prediction wei...
Trung Hau Tran, Cédric Sanza, Yves Duthen
GECCO
2008
Springer
122views Optimization» more  GECCO 2008»
15 years 2 months ago
Varying portfolio construction of stocks using genetic network programming with control nodes
A new evolutionary method named “Genetic Network Programming with Control Nodes, GNPcn” has been proposed and applied to determine the timing of buying and selling stocks. GNP...
Etsushi Ohkawa, Yan Chen, Shingo Mabu, Kaoru Shima...
LATA
2009
Springer
15 years 8 months ago
From Gene Trees to Species Trees through a Supertree Approach
Abstract. Gene trees are leaf-labeled trees inferred from molecular sequences. Due to duplication events arising in genome evolution, gene trees usually have multiple copies of som...
Celine Scornavacca, Vincent Berry, Vincent Ranwez
FOCS
2009
IEEE
15 years 8 months ago
A Complete Characterization of Statistical Query Learning with Applications to Evolvability
Statistical query (SQ) learning model of Kearns is a natural restriction of the PAC learning model in which a learning algorithm is allowed to obtain estimates of statistical prop...
Vitaly Feldman