Enviaments recents

  • A machine learning pipeline for supporting differentiation of glioblastomas from single brain metastases 

    Mocioiu, Victor; de Barros, Nuno M. Pedrosa; Ortega Martorell, Sandra; Slotboom, Johannes; Knecht, Urspeter; Arús, Carles; Vellido Alcacena, Alfredo; Julià Sapé, Margarida (I6doc.com, 2016)
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    Machine learning has provided, over the last decades, tools for knowledge extraction in complex medical domains. Most of these tools, though, are ad hoc solutions and lack the systematic approach that would be required to ...
  • Instance and feature weighted k-nearest-neighbors algorithm 

    Prat, Gabriel; Belanche Muñoz, Luis Antonio (I6doc.com, 2016)
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    We present a novel method that aims at providing a more stable selection of feature subsets when variations in the training process occur. This is accomplished by using an instance-weighting process -assigning different ...
  • Physics and machine learning: Emerging paradigms 

    Martín Guerrero, José; Lisboa, Paulo J G; Vellido Alcacena, Alfredo (I6doc.com, 2016)
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    Current research in Machine Learning (ML) combines the study of variations on well-established methods with cutting-edge breakthroughs based on completely new approaches. Among the latter, emerging paradigms from Physics ...
  • A proposal for climate change resilience management through fuzzy controllers 

    González Cárdenas, Rubén; Nebot Castells, M. Àngela; Múgica Álvarez, Francisco (SciTePress, 2016)
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    We aim towards the implementation of a set of fuzzy controllers capable to perform automated estimation of the period of time necessary to recover a resilience level through the non-linear influence of a set of interrelated ...
  • Probability ridges and distortion flows: Visualizing multivariate time series using a variational Bayesian manifold learning method 

    Tosi, Alessandra; Olier, Iván; Vellido Alcacena, Alfredo (Springer, 2014)
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    Time-dependent natural phenomena and artificial processes can often be quantitatively expressed as multivariate time series (MTS). As in any other process of knowledge extraction from data, the analyst can benefit from the ...
  • Manifold learning visualization of metabotropic glutamate receptors 

    Cárdenas Domínguez, Martha Ivón; Vellido Alcacena, Alfredo; Giraldo Arjonilla, Jesús (IOS Press, 2014)
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    G-Protein-Coupled Receptors (GPCRs) are cell membrane proteins with a key role in biological processes. GPCRs of class C, in particular, are of great interest in pharmacology. The lack of knowledge about their 3-D structures ...
  • Metrics for probabilistic geometries 

    Tosi, Alessandra; Hauberg, Søren; Vellido Alcacena, Alfredo; Lawrence, Neil D. (AUAI Press (Association for Uncertainty in Artificial Intelligence), 2014)
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    We investigate the geometrical structure of probabilistic generative dimensionality reduction models using the tools of Riemannian geometry. We explicitly define a distribution over the natural metric given by the models. ...
  • A weighted Cramér’s V Index for the assessment of stability in the fuzzy clustering of class C G protein-coupled receptors 

    Vellido Alcacena, Alfredo; Halka, Christiana; Nebot Castells, M. Àngela (Springer, 2015)
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    After decades of intensive use, K-Means is still a common choice for crisp data clustering in real-world applications, particularly in biomedicine and bioinformatics. It is well-known that different initializations of the ...
  • The extracellular N-terminal domain suffices to discriminate class C G Protein-Coupled Receptor subtypes from n-grams of their sequences 

    König, Caroline; Alquézar Mancho, René; Vellido Alcacena, Alfredo; Giraldo Arjonilla, Jesús (Institute of Electrical and Electronics Engineers (IEEE), 2015)
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    The investigation of protein functionality often relies on the knowledge of crystal 3-D structure. This structure is not always known or easily unravelled, which is the case of eukaryotic cell membrane proteins such as G ...
  • A hierarchical perspective to fuzzy inductive reasoning: an attempt to obtain more understandable fuzzy inductive reasoning rules 

    Bagherpour, Solmaz; Múgica Álvarez, Francisco; Nebot Castells, M. Àngela (2015)
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    Accés restringit per política de l'editorial
    Generalizing hypotheses based on the past data in order to predict the future is the essential core of human learning. Various successful methods and techniques have been developed so far that perform some sort of ...

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