Listar GI-GAC - Artigos por autor "Bolón-Canedo, Verónica"

Mostrando ítems 1-4 de 4

    • CUDA acceleration of MI-based feature selection methods 

      Beceiro, Bieito; González-Domínguez, Jorge; Morán-Fernández, Laura; Bolón-Canedo, Verónica; Touriño, Juan (Elsevier, 2024-08)
      [Abstract]: Feature selection algorithms are necessary nowadays for machine learning as they are capable of removing irrelevant and redundant information to reduce the dimensionality of the data and improve the quality of ...

    • CUDA-JMI: Acceleration of feature selection on heterogeneous systems 

      González-Domínguez, Jorge; Expósito, Roberto R.; Bolón-Canedo, Verónica (Elsevier, 2020-01)
      [Abstract]: Feature selection is a crucial step nowadays in machine learning and data analytics to remove irrelevant and redundant characteristics and thus to provide fast and reliable analyses. Many research works have ...

    • Multithreaded and Spark parallelization of feature selection filters 

      Eiras-Franco, Carlos; Bolón-Canedo, Verónica; Ramos Garea, Sabela; González-Domínguez, Jorge; Alonso-Betanzos, Amparo; Touriño, Juan (2016)
      [Abstract]: Vast amounts of data are generated every day, constituting a volume that is challenging to analyze. Techniques such as feature selection are advisable when tackling large datasets. Among the tools that provide ...

    • Parallel feature selection for distributed-memory clusters 

      González-Domínguez, Jorge; Bolón-Canedo, Verónica; Freire, Borja; Touriño, Juan (2019)
      [Abstract]: Feature selection is nowadays an extremely important data mining stage in the field of machine learning due to the appearance of problems of high dimensionality. In the literature there are numerous feature ...