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Mostrando ítems 1-6 de 6
Artículo
Heuristic approaches for support vector machines with the ramp loss
(Springer, 2014-03)
Recently, Support Vector Machines with the ramp loss (RLM) have attracted attention from the computational point of view. In this technical note, we propose two heuristics, the first one based on solving the continuous relaxation ...
Artículo
Biobjective sparse principal component analysis
(Academic Press Inc., 2014-08-21)
Principal Components are usually hard to interpret. Sparseness is considered as one way to improve interpretability, and thus a trade-off between variance explained by the components and sparseness is frequently sought. ...
Artículo
A nested heuristic for parameter tuning in support vector machines
(Elsevier, 2014-03)
The default approach for tuning the parameters of a Support Vector Machine (SVM) is a grid search in the parameter space. Different metaheuristics have been recently proposed as a more efficient alternative, but they have ...
Artículo
Linear separation and approximation by minimizing the sum of concave functions of distances
(Springer, 2014-03-01)
One recently proposed criterion to separate two data sets in Classification is to use a hyperplane that minimizes the sum of distances to it from all the misclassified data points, where misclassification means lying on ...
Artículo
New heuristic for harmonic means clustering
(Springer, 2014-05-06)
It is well known that some local search heuristics for K-clustering problems, such as k-means heuristic for minimum sum-of-squares clustering occasionally stop at a solution with a smaller number of clusters than the ...
Capítulo de Libro
Vulnerability assessment of spatial networks: models and solutions
(Springer, 2014)
In this paper we present a collection of combinatorial optimization problems that allows to assess the vulnerability of spatial networks in the presence of disruptions. The proposed measures of vulnerability along with the ...