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EVOW
2009
Springer
13 years 5 months ago
Conquering the Needle-in-a-Haystack: How Correlated Input Variables Beneficially Alter the Fitness Landscape for Neural Networks
Abstract. Evolutionary algorithms such as genetic programming and grammatical evolution have been used for simultaneously optimizing network architecture, variable selection, and w...
Stephen D. Turner, Marylyn D. Ritchie, William S. ...
APIN
1999
114views more  APIN 1999»
13 years 7 months ago
Evolutionary Approaches to Figure-Ground Separation
The problem of figure-ground separation is tackled from the perspective of combinatorial optimization. Previous attempts have used deterministic optimization techniques based on re...
Suchendra M. Bhandarkar, Xia Zeng
UPP
2004
Springer
14 years 27 days ago
Inverse Design of Cellular Automata by Genetic Algorithms: An Unconventional Programming Paradigm
Evolving solutions rather than computing them certainly represents an unconventional programming approach. The general methodology of evolutionary computation has already been know...
Thomas Bäck, Ron Breukelaar, Lars Willmes
GECCO
2008
Springer
143views Optimization» more  GECCO 2008»
13 years 8 months ago
A parallel evolutionary algorithm for unconstrained binary quadratic problems
In this paper an island model is described for the unconstrained Binary Quadratic Problem (BQP), which can be used with up to 2500 binary variables. Our island model uses a master...
István Borgulya
CEC
2007
IEEE
14 years 1 months ago
SAT-decoding in evolutionary algorithms for discrete constrained optimization problems
— For complex optimization problems, several population-based heuristics like Multi-Objective Evolutionary Algorithms have been developed. These algorithms are aiming to deliver ...
Martin Lukasiewycz, Michael Glaß, Christian ...