Sciweavers

GECCO
2007
Springer
189views Optimization» more  GECCO 2007»
13 years 10 months ago
A more bio-plausible approach to the evolutionary inference of finite state machines
With resemblance of finite-state machines to some biological mechanisms in cells and numerous applications of finite automata in different fields, this paper uses analogies an...
Hooman Shayani, Peter J. Bentley
GECCO
2007
Springer
163views Optimization» more  GECCO 2007»
13 years 10 months ago
Discovering event evidence amid massive, dynamic datasets
Automated event extraction remains a very difficult challenge requiring information analysts to manually identify key events of interest within massive, dynamic data. Many techniq...
Robert M. Patton, Thomas E. Potok
GECCO
2007
Springer
182views Optimization» more  GECCO 2007»
13 years 10 months ago
An analysis of the effects of population structure on scalable multiobjective optimization problems
Multiobjective evolutionary algorithms (MOEA) are an effective tool for solving search and optimization problems containing several incommensurable and possibly conflicting objec...
Michael Kirley, Robert L. Stewart
GECCO
2007
Springer
190views Optimization» more  GECCO 2007»
13 years 10 months ago
Analysis of evolutionary algorithms for the longest common subsequence problem
In the longest common subsequence problem the task is to find the longest sequence of letters that can be found as subsequence in all members of a given finite set of sequences....
Thomas Jansen, Dennis Weyland
GECCO
2007
Springer
174views Optimization» more  GECCO 2007»
13 years 10 months ago
Heuristic speciation for evolving neural network ensemble
Speciation is an important concept in evolutionary computation. It refers to an enhancements of evolutionary algorithms to generate a set of diverse solutions. The concept is stud...
Shin Ando
INFOCOM
2007
IEEE
13 years 10 months ago
Evolutionary Approaches To Minimizing Network Coding Resources
Abstract— We consider the problem of minimizing the resources used for network coding while achieving the desired throughput in a multicast scenario. Since this problem is NPhard...
Minkyu Kim, Muriel Médard, Varun Aggarwal, ...
CEC
2007
IEEE
13 years 10 months ago
Concerning the potential of evolutionary support vector machines
— Within the present paper, we put forward a novel hybridization between support vector machines and evolutionary algorithms. Evolutionary support vector machines consider the cl...
Ruxandra Stoean, Mike Preuss, Catalin Stoean, Dumi...
CEC
2007
IEEE
13 years 10 months ago
A rigorous view on neutrality
Abstract—Motivated by neutrality observed in natural evolution often redundant encodings are used in evolutionary algorithms. Many experimental studies have been carried out on t...
Benjamin Doerr, Michael Gnewuch, Nils Hebbinghaus,...
GECCO
2009
Springer
132views Optimization» more  GECCO 2009»
13 years 11 months ago
Bringing evolutionary computation to industrial applications with guide
Evolutionary Computation is an exciting research field with the power to assist researchers in the task of solving hard optimization problems (i.e., problems where the exploitabl...
Luís Da Costa, Marc Schoenauer
CEC
2009
IEEE
13 years 11 months ago
Comparing parameter tuning methods for evolutionary algorithms
Abstract— Tuning the parameters of an evolutionary algorithm (EA) to a given problem at hand is essential for good algorithm performance. Optimizing parameter values is, however,...
Selmar K. Smit, A. E. Eiben