Ponències/Comunicacions de congressos

Enviaments recents

  • Bridging deep and kernel methods 

    Belanche Muñoz, Luis Antonio; Ruiz Costa-Jussà, Marta (2017)
    Text en actes de congrés
    Accés restringit per política de l'editorial
    There has been some exciting major progress in recent years in data analysis methods, including a variety of deep learning architectures, as well as further advances in kernel-based learning methods, which have demonstrated ...

  • Benchmarking the selection of the hidden-layer weights in extreme learning machines 

    Romero Merino, Enrique (Institute of Electrical and Electronics Engineers (IEEE), 2017)
    Text en actes de congrés
    Accés obert
    Recent years have seen a growing interest in neural networks whose hidden-layer weights are randomly selected, such as Extreme Learning Machines (ELMs). These models are motivated by their ease of development, high ...

  • A prospective fuzzy approach for the development of integral seismic risk scenarios for Barcelona, Spain 

    González Cárdenas, Rubén; Múgica Álvarez, Francisco; Nebot Castells, M. Àngela (SciTePress, 2017)
    Text en actes de congrés
    Accés restringit per política de l'editorial
    We create a set of synthetic seismic risk scenarios by combining stochastic seismic simulations with social fragility indicators by mean of a fuzzy Mamdani type inference nested-model. The original values of the social ...

  • Modeling a flue-gas desulfurization plant with a fuzzy methodology to optimize the SO2 absorption process 

    Escobet Canal, Antoni; Nebot Castells, M. Àngela; Múgica Álvarez, Francisco; Gamisans Noguera, Javier; Guimerà Villalba, Xavier (2017)
    Text en actes de congrés
    Accés restringit per política de l'editorial

  • Bayesian semi non-negative matrix factorisation 

    Vilamala Muñoz, Albert; Vellido Alcacena, Alfredo; Belanche Muñoz, Luis Antonio (I6doc.com, 2016)
    Text en actes de congrés
    Accés obert
    Non-negative Matrix Factorisation (NMF) has become a standard method for source identification when data, sources and mixing coefficients are constrained to be positive-valued. The method has recently been extended to allow ...

  • A methodological approach for algorithmic composition systems' parameter spaces aesthetic exploration 

    Paz Ortiz, Iván; Nebot Castells, M. Àngela; Romero Merino, Enrique; Múgica Álvarez, Francisco; Vellido Alcacena, Alfredo (Institute of Electrical and Electronics Engineers (IEEE), 2017)
    Comunicació de congrés
    Accés obert
    Algorithmic composition is the process of creating musical material by means of formal methods. As a consequence of its design, algorithmic composition systems are (explicitly or implicitly) described in terms of parameters. ...

  • A decision making support tool: The resilience management fuzzy controller 

    González Cardenas, Rubén; Nebot Castells, M. Àngela; Múgica Álvarez, Francisco; Vellido Alcacena, Alfredo (Institute of Electrical and Electronics Engineers (IEEE), 2017)
    Text en actes de congrés
    Accés obert
    In this paper a fuzzy controller capable to perform an automated estimation of the period of time necessary to recover a resilience level is proposed. Estimations where made by considering realistic time-dependent action ...

  • Multivariate dynamic kernels for financial time series forecasting 

    Peña, Mauricio; Arratia Quesada, Argimiro Alejandro; Belanche Muñoz, Luis Antonio (Springer, 2016)
    Text en actes de congrés
    Accés obert
    We propose a forecasting procedure based on multivariate dynamic kernels, with the capability of integrating information measured at different frequencies and at irregular time intervals in financial markets. A data ...

  • Automated quality control for proton magnetic resonance spectroscopy data using convex non-negative matrix factorization 

    Mocioiu, Victor; Kyathanahally, Sreenath P.; Arús, Carles; Vellido Alcacena, Alfredo; Julià Sapé, Margarida (Springer, 2016)
    Text en actes de congrés
    Accés obert
    Proton Magnetic Resonance Spectroscopy (1H MRS) has proven its diagnostic potential in a variety of conditions. However, MRS is not yet widely used in clinical routine because of the lack of experts on its diagnostic ...

  • 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)
    Text en actes de congrés
    Accés obert
    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)
    Text en actes de congrés
    Accés obert
    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)
    Text en actes de congrés
    Accés obert
    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 ...

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