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GECCO
2006
Springer
188views Optimization» more  GECCO 2006»
15 years 8 months ago
Dynamic multi-objective optimization with evolutionary algorithms: a forward-looking approach
This work describes a forward-looking approach for the solution of dynamic (time-changing) problems using evolutionary algorithms. The main idea of the proposed method is to combi...
Iason Hatzakis, David Wallace
GECCO
2006
Springer
121views Optimization» more  GECCO 2006»
15 years 8 months ago
A splicing/decomposable encoding and its novel operators for genetic algorithms
In this paper, we introduce a new genetic representation -- a splicing/decomposable (S/D) binary encoding, which was proposed based on some theoretical guidance and existing recom...
Yong Liang, Kwong-Sak Leung, Kin-Hong Lee
KDD
2010
ACM
275views Data Mining» more  KDD 2010»
15 years 8 months ago
Combined regression and ranking
Many real-world data mining tasks require the achievement of two distinct goals when applied to unseen data: first, to induce an accurate preference ranking, and second to give g...
D. Sculley
EVOW
2010
Springer
15 years 7 months ago
Improving Multi-Relief for Detecting Specificity Residues from Multiple Sequence Alignments
A challenging problem in bioinformatics is the detection of residues that account for protein function specificity, not only in order to gain deeper insight in the nature of functi...
Elena Marchiori
GECCO
2010
Springer
184views Optimization» more  GECCO 2010»
15 years 7 months ago
A mono surrogate for multiobjective optimization
Most surrogate approaches to multi-objective optimization build a surrogate model for each objective. These surrogates can be used inside a classical Evolutionary Multiobjective O...
Ilya Loshchilov, Marc Schoenauer, Michèle S...