GI-LIDIA - Artigos: Envíos recentes

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    • La inteligencia artificial y la prospectiva 

      Alonso-Betanzos, Amparo (Colegio de Economistas de La Coruña, 2023)
      [Resumen]: La Inteligencia Artificial (IA) es una de las tecnologías que más está influyendo en el actual tránsito a la llamada Sociedad 5.0, la sociedad creativa e inteligente del futuro, que la Unión Europea, junto con ...

    • Towards federated feature selection: Logarithmic division for resource-conscious methods 

      Suárez-Marcote, Samuel; Morán-Fernández, Laura; Bolón-Canedo, Verónica (Elsevier, 2024)
      [Abstract]: Feature selection is a popular preprocessing step to reduce the dimensionality of the data while preserving the important information. In this paper, we propose an efficient and green feature selection method ...

    • A review of green artificial intelligence: Towards a more sustainable future 

      Bolón-Canedo, Verónica; Morán-Fernández, Laura; Cancela, Brais; Alonso-Betanzos, Amparo (Elsevier B.V., 2024-09-28)
      [Abstract]: Green artificial intelligence (AI) is more environmentally friendly and inclusive than conventional AI, as it not only produces accurate results without increasing the computational cost but also ensures that ...

    • Sustainable transparency on recommender systems: Bayesian ranking of images for explainability 

      Paz Ruza, Jorge; Alonso-Betanzos, Amparo; Guijarro-Berdiñas, Bertha; Cancela, Brais; Eiras-Franco, Carlos (Elsevier B.V., 2024-11)
      [Abstract]: Recommender Systems have become crucial in the modern world, commonly guiding users towards relevant content or products, and having a large influence over the decisions of users and citizens. However, ensuring ...

    • Finding a needle in a haystack: insights on feature selection for classification tasks 

      Morán-Fernández, Laura; Bolón-Canedo, Verónica (Springer, 2024-04)
      [Abstract]: The growth of Big Data has resulted in an overwhelming increase in the volume of data available, including the number of features. Feature selection, the process of selecting relevant features and discarding ...