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» On improving approximate solutions by evolutionary algorithm...
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ENC
2005
IEEE
15 years 7 months ago
Saving Evaluations in Differential Evolution for Constrained Optimization
Generally, evolutionary algorithms require a large number of evaluations of the objective function in order to obtain a good solution. This paper presents a simple approach to sav...
Efrén Mezura-Montes, Carlos A. Coello Coell...
ACL
2007
15 years 3 months ago
Inducing Combinatory Categorial Grammars with Genetic Algorithms
This paper proposes a novel approach to the induction of Combinatory Categorial Grammars (CCGs) by their potential affinity with the Genetic Algorithms (GAs). Specifically, CCGs...
Elias Ponvert
ICALP
2010
Springer
15 years 6 months ago
Network Design via Core Detouring for Problems without a Core
Some of the currently best-known approximation algorithms for network design are based on random sampling. One of the key steps of such algorithms is connecting a set of source nod...
Fabrizio Grandoni, Thomas Rothvoß
NIPS
2008
15 years 3 months ago
Bayesian Experimental Design of Magnetic Resonance Imaging Sequences
We show how improved sequences for magnetic resonance imaging can be found through optimization of Bayesian design scores. Combining approximate Bayesian inference and natural ima...
Matthias W. Seeger, Hannes Nickisch, Rolf Pohmann,...
ICML
2004
IEEE
16 years 2 months ago
Generalized low rank approximations of matrices
The problem of computing low rank approximations of matrices is considered. The novel aspect of our approach is that the low rank approximations are on a collection of matrices. W...
Jieping Ye