• A Machine Learning Solution for Distributed Environments and Edge Computing 

      Penas-Noce, Javier; Fontenla-Romero, Óscar; Guijarro-Berdiñas, Bertha (MDPI AG, 2019-08-09)
      [Abstract] In a society in which information is a cornerstone the exploding of data is crucial. Thinking of the Internet of Things, we need systems able to learn from massive data and, at the same time, being inexpensive ...
    • Dealing with heterogeneity in the context of distributed feature selection for classification 

      Morillo-Salas, José Luis; Bolón-Canedo, Verónica; Alonso-Betanzos, Amparo (Springer, 2021)
      [Abstract]: Advances in the information technologies have greatly contributed to the advent of larger datasets. These datasets often come from distributed sites, but even so, their large size usually means they cannot be ...
    • Insights into distributed feature ranking 

      Bolón-Canedo, Verónica; Sechidis, Konstantinos; Sánchez-Maroño, Noelia; Alonso-Betanzos, Amparo; Brown, Gavin (Elsevier, 2019)
      [Abstract]: In an era in which the volume and complexity of datasets is continuously growing, feature selection techniques have become indispensable to extract useful information from huge amounts of data. However, existing ...