Listar GI-LIDIA - Artigos por autor "Alonso-Betanzos, Amparo"

Mostrando ítems 21-24 de 24

    • On the scalability of feature selection methods on high-dimensional data 

      Bolón-Canedo, Verónica; Rego-Fernández, Diego; Peteiro Barral, Diego; Alonso-Betanzos, Amparo; Guijarro-Berdiñas, Bertha; Sánchez-Maroño, Noelia (Springer, 2018)
      [Abstract]: Lately, derived from the explosion of high dimensionality, researchers in machine learning became interested not only in accuracy, but also in scalability. Although scalability of learning methods is a trending ...

    • Scalable Feature Selection Using ReliefF Aided by Locality-Sensitive Hashing 

      Eiras-Franco, Carlos; Guijarro-Berdiñas, Bertha; Alonso-Betanzos, Amparo; Bahamonde, Antonio (Wiley, 2021)
      [Abstract] Feature selection algorithms, such as ReliefF, are very important for processing high-dimensionality data sets. However, widespread use of popular and effective such algorithms is limited by their computational ...

    • Simulating the Role of Norms in Processes of Social Innovation: Three Case Studies 

      Jager, Wander; Guijarro-Berdiñas, Bertha; Bouman, Loes; Antosz, Patrycja; Alonso-Betanzos, Amparo; Salt, Douglas; Polhill, J. Gary; Rodríguez Arias, Alejandro; Sánchez-Maroño, Noelia (SimSoc Consortium, 2024-01)
      [Absctract]: Norms and values are critical drivers in social innovation processes, such as community projects on sustainable energy. Simulating such processes could help uncover conditions that support these social ...

    • Wavefront Marching Methods: A Unified Algorithm to Solve Eikonal and Static Hamilton-Jacobi Equations 

      Cancela, Brais; Alonso-Betanzos, Amparo (IEEE, 2019-12)
      [Abstract]: This paper presents a unified propagation method for dealing with both the classic Eikonal equation, where the motion direction does not affect the propagation, and the more general static Hamilton-Jacobi ...