Recent Submissions

  • Comparing error minimized extreme learning machines and support vector sequential feed-forward neural networks 

    Romero Merino, Enrique; Alquézar Mancho, René (2010-06)
    External research report
    Open Access
    Recently, error minimized extreme learning machines (EM-ELMs) have been proposed as a simple and efficient approach to build single-hidden-layer feed-forward networks (SLFNs) sequentially. They add random hidden nodes one ...
  • Understanding (dis)similarity measures 

    Belanche Muñoz, Luis Antonio (2013-01)
    External research report
    Open Access
    Intuitively, the concept of similarity is the notion to measure an inexact matching between two entities of the same reference set. The notions of similarity and its close relative dissimilarity are widely used in many ...
  • Visual-FIR for ozone modeling and prediction 

    Nebot Castells, M. Àngela; Múgica, Violeta; Escobet Canal, Antoni (2007-04)
    External research report
    Open Access
    Air pollution is one of the most important environmental problems in urban areas, being extremely critical in Mexico City. The main air pollution problem that has been identified in Mexico City metropolitan area is the ...
  • Modelado de las concentraciones locales de ozono en la Zona Centro del Area Metropolitana de la Ciudad de México 

    Acosta, Jesús; Nebot Castells, M. Àngela; Fuertes Armengol, José Mª (2006-03)
    External research report
    Open Access
    La contaminación del aire constituye el problema medioambiental de principal atención en las áreas urbanas debido a que afecta la salud de la población, en especial a la de los niños. Es por ello, que la construcción de ...
  • A variational formulation for GTM through time: Theoretical foundations 

    Olier Caparroso, Iván; Vellido Alcacena, Alfredo (2007-10)
    External research report
    Open Access
    Generative Topographic Mapping (GTM) is a latent variable model that, in its standard version, was conceived to provide clustering and visualization of multivariate, real-valued, i.i.d. data. It was also extended to deal ...
  • A variational Bayesian formulation for GTM: Theoretical foundations 

    Olier Caparroso, Iván; Vellido Alcacena, Alfredo (2007-09)
    External research report
    Open Access
    Generative Topographic Mapping (GTM) is a non-linear latent variable model of the manifold learning family that provides simultaneous visualization and clustering of high-dimensional data. It was originally formulated as ...
  • Predictive models in churn data mining: a review 

    García, David L.; Vellido Alcacena, Alfredo; Nebot Castells, M. Àngela (2007-01)
    External research report
    Open Access
    The development of predictive models of customer abandonment plays a central role in any churn management strategy. These models can be developed using either qualitative approaches or can take a data-centred point of view. ...
  • Customer continuity management as a foundation for churn data mining 

    García, David L.; Vellido Alcacena, Alfredo; Nebot Castells, M. Àngela (2007-01)
    External research report
    Open Access
    This report lays the first theoretical foundations for a research program on analytical churn management. In the current hypercompetitive business scenario, firms have to bend over backwards in their strategies both to ...
  • Elements of generative manifold learning for semi-supervised tasks 

    Cruz, Raúl; Vellido Alcacena, Alfredo (2007-01)
    External research report
    Open Access
    For many real-world application problems, the availability of data labels for supervised learning is rather limited. It is often the case that a limited number of labelled cases is accompanied by a larger number of unlabeled ...
  • Método multiobjetivo de aprendizaje para razonamiento inductivo difuso 

    Acosta, Jesús; Nebot Castells, M. Àngela; Fuertes Armengol, José Mª (2006-10)
    External research report
    Open Access
    It has been recognized in various studies that the variations in the granularity (number of classes per variable) and the membership functions have a significant effect in the behaviour of the fuzzy systems. The FIR ...

View more