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» Generalized crowding for genetic algorithms
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BMCBI
2004
167views more  BMCBI 2004»
14 years 9 months ago
Feature selection for splice site prediction: A new method using EDA-based feature ranking
Background: The identification of relevant biological features in large and complex datasets is an important step towards gaining insight in the processes underlying the data. Oth...
Yvan Saeys, Sven Degroeve, Dirk Aeyels, Pierre Rou...
86
Voted
GECCO
2009
Springer
142views Optimization» more  GECCO 2009»
15 years 4 months ago
A stopping criterion based on Kalman estimation techniques with several progress indicators
The need for a stopping criterion in MOEA’s is a repeatedly mentioned matter in the domain of MOOP’s, even though it is usually left aside as secondary, while stopping criteri...
José Luis Guerrero, Jesús Garc&iacut...
CIKM
2007
Springer
15 years 3 months ago
Randomized metric induction and evolutionary conceptual clustering for semantic knowledge bases
We present an evolutionary clustering method which can be applied to multi-relational knowledge bases storing resource annotations expressed in the standard languages for the Sema...
Nicola Fanizzi, Claudia d'Amato, Floriana Esposito
COCOON
2008
Springer
14 years 11 months ago
Haplotype Inferring Via Galled-Tree Networks Is NP-Complete
The problem of determining haplotypes from genotypes has gained considerable prominence in the research community since the beginning of the HapMap project. Here the focus is on de...
Arvind Gupta, Ján Manuch, Ladislav Stacho, ...
GECCO
2008
Springer
183views Optimization» more  GECCO 2008»
14 years 10 months ago
UMDAs for dynamic optimization problems
This paper investigates how the Univariate Marginal Distribution Algorithm (UMDA) behaves in non-stationary environments when engaging in sampling and selection strategies designe...
Carlos M. Fernandes, Cláudio F. Lima, Agost...