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Artículo
Binarized support vector machines
(INFORMS (Institute for Operations Research and Management Sciences), 2010)
The widely used Support Vector Machine (SVM) method has shown to yield very good results in Supervised Classification problems. Other methods such as Classification Trees have become more popular among practitioners than ...
Artículo
Supervised classification and mathematical optimization
(Elsevier, 2013-01)
Data Mining techniques often ask for the resolution of optimization problems. Supervised Classification, and, in particular, Support Vector Machines, can be seen as a paradigmatic instance. In this paper, some links between ...
Artículo
Problemas de clasificación y optimización
(Real Academia Sevillana de Ciencias, 2003)
El desarrollo de técncias que permitan clasificar entes (seres vivos, elementos, problemas, ... ) en distintas categorías ha sido recurrente en diversas ramas del saber. La creación y difusión de grandes bases de datos y ...
Artículo
Robust newsvendor problem with autoregressive demand
(Elsevier, 2016-04)
This paper explores the classic single-item newsvendor problem under a novel setting which combines temporal dependence and tractable robust optimization. First, the demand is modeled as a time series which follows an ...
Artículo
On minimax-regret Huff location models
(Elsevier, 2011-01)
We address the following single-facility location problem: a firm is entering into a market by locating one facility in a region of the plane. The demand captured from each user by the facility will be proportional to the ...
Artículo
Multi-group support vector machines with measurement costs a biobjective approach
(Elsevier, 2008-03)
Support Vector Machine has shown to have good performance in many practical classification settings. In this paper we propose, for multi-group classification, a biobjective optimization model in which we consider not only ...
Artículo
A sparsity-controlled vector autoregressive model
(Oxford University Press, 2017-04)
Vector autoregressive (VAR) models constitute a powerful and well studied tool to analyze multivariate time series. Since sparseness, crucial to identify and visualize joint dependencies and relevant causalities, is not ...
Artículo
Continuous location problems and Big Triangle Small Triangle: constructing better bounds
(Springer, 2009-11)
The Big Triangle Small Triangle method has shown to be a powerful global optimization procedure to address continuous location problems. In the paper published in J. Global Optim. (37:305–319, 2007), Drezner proposes a ...
Artículo
Detecting relevant variables and interactions in supervised classification
(Elsevier, 2011-08-16)
The widely used Support Vector Machine (SVM) method has shown to yield good results in Supervised Classification problems. When the interpretability is an important issue, then classification methods such as Classification ...
Artículo
Clustering categories in support vector machines
(Elsevier, 2016-02)
The support vector machine (SVM) is a state-of-the-art method in supervised classification. In this paper the Cluster Support Vector Machine (CLSVM) methodology is proposed with the aim to increase the sparsity of the SVM ...