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GECCO
2005
Springer
136views Optimization» more  GECCO 2005»
14 years 1 months ago
Preventing overfitting in GP with canary functions
Overfitting is a fundamental problem of most machine learning techniques, including genetic programming (GP). Canary functions have been introduced in the literature as a concept ...
Nate Foreman, Matthew P. Evett
GECCO
2005
Springer
118views Optimization» more  GECCO 2005»
14 years 1 months ago
The Push3 execution stack and the evolution of control
The Push programming language was developed for use in genetic and evolutionary computation systems, as the representation within which evolving programs are expressed. It has bee...
Lee Spector, Jon Klein, Maarten Keijzer
GECCO
2006
Springer
143views Optimization» more  GECCO 2006»
13 years 11 months ago
Hybrid search for cardinality constrained portfolio optimization
In this paper, we describe how a genetic algorithm approach added to a simulated annealing (SA) process offers a better alternative to find the mean variance frontier in the portf...
Miguel A. Gomez, Carmen X. Flores, Maria A. Osorio
GECCO
2008
Springer
133views Optimization» more  GECCO 2008»
13 years 8 months ago
Automatic generation of XSLT stylesheets using evolutionary algorithms
This paper introduces a procedure based on genetic programming to evolve XSLT programs (usually called stylesheets or logicsheets). XSLT is a general purpose, document-oriented fu...
Pablo García-Sánchez, Juan Juli&aacu...
VIS
2003
IEEE
145views Visualization» more  VIS 2003»
14 years 9 months ago
Signed Distance Transform Using Graphics Hardware
This paper presents a signed distance transform algorithm using graphics hardware, which computes the scalar valued function of the Euclidean distance to a given manifold of co-di...
Christian Sigg, Markus H. Gross, Ronald Peikert