Listar GI-IRlab-Artigos por data de publicación

Mostrando ítems 21-26 de 26

    • On the semantics of hybrid ASP systems based on Clingo 

      Cabalar, Pedro; Fandinno, Jorge; Schaub, Torsten; Wanko, Philipp (MDPI, 2023-03)
      [Abstract]: Over the last decades, the development of Answer Set Programming (ASP) has brought about an expressive modeling language powered by highly performant systems. At the same time, it gets more and more difficult ...

    • 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 ...

    • Protein structure prediction with energy minimization and deep learning approaches 

      Filgueiras Rilo, Juan Luis; Varela, Daniel; Santos Reyes, José (Springer Science and Business Media B.V., 2023-12)
      [Abstract]: In this paper we discuss the advantages and problems of two alternatives for ab initio protein structure prediction. On one hand, recent approaches based on deep learning, which have significantly improved ...

    • 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 ...

    • 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 ...

    • 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 ...