Now showing items 1-20 of 67

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      A biobjective method for sample allocation in stratified sampling  [Article]

      Carrizosa Priego, Emilio José; Romero Morales, María Dolores (Elsevier, 2007-03-01)
      The two main and contradicting criteria guiding sampling design are accuracy of estimators and sampling costs. In stratified random sampling, the sample size must be allocated to strata in order to optimize both objectives. ...
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      A heuristic method for simultaneous tower and pattern-free field optimization on solar power systems  [Article]

      Carrizosa Priego, Emilio José; Domínguez Bravo, Carmen Ana; Fernández Cara, Enrique; Quero García, Manuel (Elsevier, 2015-05)
      A heuristic method for optimizing a solar power tower system is proposed, in which both heliostat field (heliostat locations and number) and the tower (tower height and receiver size) are simultaneously considered. Maximizing ...
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      A nested heuristic for parameter tuning in support vector machines  [Article]

      Carrizosa Priego, Emilio José; Martín Barragán, Belén; Romero Morales, María Dolores (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 ...
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      A new multivariate data analysis model: constrained Naïve Bayes  [Master's Thesis]

      Sillero Denamiel, María Remedios (2016-06-24)
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      A sparsity-controlled vector autoregressive model  [Article]

      Carrizosa Priego, Emilio José; Olivares Nadal, Alba Victoria; Ramírez Cobo, Josefa (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 ...
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      Alternating local search based VNS for linear classification  [Article]

      Plastria, Frank; Bruyne, Steven de; Carrizosa Priego, Emilio José (Springer, 2010-02)
      We consider the linear classification method consisting of separating two sets of points in d-space by a hyperplane. We wish to determine the hyperplane which minimises the sum of distances from all misclassified points ...
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      An optimization tool to design the field of a solar power tower plant allowing heliostats of different sizes  [Article]

      Carrizosa Priego, Emilio José; Domínguez Bravo, Carmen Ana; Fernández Cara, Enrique; Quero García, Manuel (Wiley, 2017)
      The design of a Solar Power Tower plant involves the optimization of the heliostat field layout. Fields are usually designed to have all heliostats of identical size. Although the use of a single heliostat size has been ...
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      Aprendizaje supervisado mediante random forests  [Master's Thesis]

      Molero del Río, María Cristina (2017-06)
      Muchos problemas de la vida real pueden modelarse como problemas de clasificación, tales como la detección temprana de enfermedades o la concesión de crédito a un cierto individuo. La Clasificación Supervisada se encarga ...
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      Binarized support vector machines  [Article]

      Carrizosa Priego, Emilio José; Martín Barragán, Belén; Romero Morales, María Dolores (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 ...
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      Classification and regression with functional data: a mathematical optimization approach.  [PhD Thesis]

      Jiménez Cordero, María Asunción (2019-02-15)
      El objetivo de esta tesis doctoral es desarrollar nuevos métodos para la clasificación y regresión supervisada en el Análisis de Datos Funcionales. En particular, las herramientas de Optimización Matemática analizadas en ...
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      Clustering categories in support vector machines  [Article]

      Carrizosa Priego, Emilio José; Nogales Gómez, Amaya; Romero Morales, María Dolores (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 ...
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      Constrained support vector machines theory and applications to health science  [Master's Thesis]

      Benítez Peña, Sandra (2016-06-24)
      En los últimos años, la ciencia de los datos se ha convertido en una herramienta muy importante para tratar datos, así como para descubrir patrones y generar información útil en la toma de decisiones. Una de las tareas más ...
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      Continuous location problems and Big Triangle Small Triangle: constructing better bounds  [Article]

      Blanquero Bravo, Rafael; Carrizosa Priego, Emilio José (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 ...
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      Cost-sensitive feature selection for support vector machines  [Article]

      Benítez Peña, Sandra; Blanquero Bravo, Rafael; Carrizosa Priego, Emilio José; Ramírez Cobo, Josefa (Elsevier, 2018-03)
      Feature Selection (FS) is a crucial procedure in Data Science tasks such as Classification, since it identifies the relevant variables, making thus the classification procedures more interpretable and more effective by ...
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      Detecting relevant variables and interactions in supervised classification  [Article]

      Carrizosa Priego, Emilio José; Martín Barragán, Belén; Romero Morales, María Dolores (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 ...
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      Dimensionality Reduction for Classification: Comparison of Techniques and Dimension Choice  [Chapter of Book]

      Plastria, Frank; Bruyne, Steven de; Carrizosa Priego, Emilio José (Springer, 2008)
      We investigate the effects of dimensionality reduction using different techniques and different dimensions on six two-class data sets with numerical attributes as pre-processing for two classification algorithms. Besides ...
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      Dominating sets for convex functions with some applications  [Article]

      Carrizosa Priego, Emilio José; Frenk, Johannes B. G. (Springer, 1998-02)
      A number of optimization methods require as a rst step the construction of a dominating set (a set containing an optimal solution) enjoying properties such as compactness or convexity. In this note we address the problem ...
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      Enhancing robustness and sparsity via mathematical optimization  [PhD Thesis]

      Olivares Nadal, Alba Victoria (2016-09-22)
      Esta tesis se centra en derivar métodos robustos o dispersos bajo la perspectiva de la optimización para problemas que tradicionalmente se engloban en los campos de la Estadística o de la Investigación Operativa. Concretamente, ...
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      Field-design optimization with triangular heliostat pods  [Article]

      Domínguez Bravo, Carmen Ana; Bode, Sebastian James; Heiming, Gregor; Richter, Pascal; Carrizosa Priego, Emilio José; Fernández Cara, Enrique; Frank, Martin; Gauché, Paul (American Institute of Physics, 2016-05)
      In this paper the optimization of a heliostat field with triangular heliostat pods is addressed. The use of structures which allow the combination of several heliostats into a common pod system aims to reduce the high ...