Mostrando ítems 1-5 de 36

    • Syntactic ASP forgetting with forks 

      Aguado, Felicidad; Cabalar, Pedro; Fandiño, Jorge; Pearce, David; Pérez, Gilberto; Vidal, Concepción (Elsevier, 2024-01)
      [Abstract]: Answer Set Programming (ASP) constitutes nowadays one of the most successful paradigms for practical Knowledge Representation and declarative problem solving. The formal analysis of ASP programs is essential ...
    • Variable selection in the prediction of business failure using genetic programming 

      Beade, José; Rodríguez Seijo, José Manuel; Santos Reyes, José (Elsevier B.V., 2024-04-08)
      This study focuses on dimensionality reduction by variable selection in business failure prediction models. A new method of dimensionality reduction by variable selection using Genetic Programming is proposed, which takes ...
    • Model Explanation via Support Graphs 

      Cabalar, Pedro; Muñiz, Brais (Cambridge Univeristy Press, 2024-02)
      [Absctract]: In this note, we introduce the notion of support graph to define explanations for any model of a logic program. An explanation is an acyclic support graph that, for each true atom in the model, induces a proof ...
    • Computational approaches to Explainable Artificial Intelligence: Advances in theory, applications and trends 

      Górriz, Juan M.; Álvarez-Illán, I.; Álvarez-Marquina, Agustín; Arco, Juan Eloy; Atzmueller, Martin; Ballarini, F.; Barakova, Emilia; Bologna, Guido; Duro, Richard J. Richard J. xxx; Santos Reyes, José (Elsevier, 2023-12)
      [Abstract]: Deep Learning (DL), a groundbreaking branch of Machine Learning (ML), has emerged as a driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted in complex and non-linear ...
    • M3DISEEN: A novel machine learning approach for predicting the 3D printability of medicines 

      Elbadawi, Moe; Muñiz, Brais; Gavins, Francesca K.H.; Ong, Jun Jie; Gaisford, Simon; Pérez, Gilberto; Basit, Abdul W; Cabalar, Pedro; Goyanes, Álvaro (Elsevier B.V., 2020-11)
      [Abstract]: Artificial intelligence (AI) has the potential to reshape pharmaceutical formulation development through its ability to analyze and continuously monitor large datasets. Fused deposition modeling (FDM) ...