Enviaments recents

  • A deep learning-based method for uncovering GPCR ligand-induced conformational states using interpretability techniques 

    Gutiérrez Mondragón, Mario Alberto; König, Caroline; Vellido Alcacena, Alfredo (Springer, 2022)
    Text en actes de congrés
    Accés obert
    There is increasing interest in the development of tools for investigating the protein ligand space. Understanding the underlying mechanisms of G protein-coupled receptors (GPCR) in the ligand-binding process is of particular ...
  • The importance of interpretability and visualization in ML for medical applications 

    Vellido Alcacena, Alfredo (2021)
    Comunicació de congrés
    Accés obert
    Many areas of science have made a sharp transition towards data-dependent methods, enabled by simultaneous advances in data acquisition and the development of networked system technologies. This is particularly clear in ...
  • The coming of age of interpretable and explainable machine learning models 

    Lisboa, Paulo; Saralajew, Sascha; Vellido Alcacena, Alfredo; Villmann, Thomas (I6doc.com, 2021)
    Text en actes de congrés
    Accés obert
    Machine learning-based systems are now part of a wide array of real-world applications seamlessly embedded in the social realm. In the wake of this realisation, strict legal regulations for these systems are currently being ...
  • Off-the-grid: Fast and effective hyperparameter search for kernel clustering 

    Ordozgoiti Rubio, Bruno; Belanche Muñoz, Luis Antonio (Springer, 2020)
    Text en actes de congrés
    Accés obert
    Kernel functions are a powerful tool to enhance the k-means clustering algorithm via the kernel trick. It is known that the parameters of the chosen kernel function can have a dramatic impact on the result. In supervised ...
  • Fault detection and identification in a fuel cell system 

    Escobet Canal, Antoni; Nebot Castells, M. Àngela (IOS Press, 2009)
    Text en actes de congrés
    Accés restringit per política de l'editorial
    In this work a fault diagnosis system for non-linear plants based on fuzzy logic, called VisualBlock-FIR, is presented and applied to an energy generation system based on fuel cells. VisualBlock-FIR runs under the Simulink ...
  • Interpreting response to TMZ therapy in murine GL261 glioblastoma by combining Radiomics, Convex-NMF and feature selection in MRI/MRSI data analysis 

    Nuñez Vivero, Luis Miguel; Julia Sape, Margarida; Romero Merino, Enrique; Arus Caraltó, Carles; Vellido Alcacena, Alfredo; Candiota Silveira, Ana Paula (Institute of Electrical and Electronics Engineers (IEEE), 2020)
    Text en actes de congrés
    Accés obert
    Machine learning (ML) methods have shown great potential for the analysis of data involved in medical decisions. However, for these methods to be incorpored in the medical pipeline, they must be made interpretable not only ...
  • Similarity-based heterogeneous neuron models 

    Belanche Muñoz, Luis Antonio (IOS Press, 2000)
    Text en actes de congrés
    Accés obert
    This paper introduces a general class of neuron models, accepting heterogeneous inputs in the form of mixtures of continuous (crisp or fuzzy) numbers, linguistic information, and discrete (either ordinal or nominal) ...
  • Fuzzy inputs and missing data in similarity-based heterogeneous neural networks 

    Belanche Muñoz, Luis Antonio; Valdés Ramos, Julio José (Springer, 1999)
    Text en actes de congrés
    Accés obert
    Fuzzy heterogeneous networks are recently introduced neural network models composed of neurons of a general class whose inputs and weights are mixtures of continuous variables (crisp and/or fuzzy) with discrete quantities, ...
  • On some strategies for missing values in positive semidefinite matrices 

    Belanche Muñoz, Luis Antonio; Vázquez García, Miguel (Thompson, 2005)
    Text en actes de congrés
    Accés obert
    This article presents our work on missing values in Positive Semi-Definite or PSD matrices. We show how simple properties of PSD matrices can be used to deal with missing values. We study several situations and investigate ...
  • A thermodynamic algorithm for feature selection 

    Belanche Muñoz, Luis Antonio; González Navarro, Félix Fernando (Thomson Editores Spain, 2007)
    Text en actes de congrés
    Accés obert
    The main purpose of Feature Selection (FS) is to find a reduced subset of attributes from a data set described by a feature set. This implies a search process in the space of possible solutions, trying to optimize an ...
  • Un algoritmo para el cálculo de la relevancia entrópica multivariada y su uso en la selección de variables 

    González Navarro, Félix Fernando; Belanche Muñoz, Luis Antonio (Thomson Editores Spain, 2007)
    Text en actes de congrés
    Accés obert
    La reducción de la dimensionalidad mediante la selección de variables es uno de los pasos fundamentales del preprocesado de datos, como fase previa al análisis de información y descubrimiento de conocimiento. De entre los ...
  • TFS: a thermodynamical search algorithm for feature subset selection 

    González Navarro, Félix Fernando; Belanche Muñoz, Luis Antonio (Thomson Editores Spain, 2007)
    Text en actes de congrés
    Accés obert
    This work tackles the problem of selecting a subset of features in an inductive learning setting, by introducing a novel Thermodynamic Feature Selection algorithm (TFS). Given a suitable objective function, the algorithm ...

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