Information Retrieval Lab (IRlab): Envíos recentes

Mostrando ítems 11-15 de 49

    • Metric dynamic equilibrium logic 

      Becker, Arvid; Cabalar, Pedro; Diéguez Lodeiro, Martín; Farinas del Cerro, Luis; Schaub, Torsten; Schuhmann, Anna (Taylor and Francis Ltd., 2023)
      [Abstract]: In temporal extensions of Answer Set Programming (ASP) based on linear-time, the behaviour of dynamic systems is captured by sequences of states. While this representation reflects their relative order, it ...

    • 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 ...

    • Delving into the Depths: Evaluating Depression Severity through BDI-biased Summaries 

      Aragón, Mario Ezra; Parapar, Javier; Losada, David E. (Association for Computational Linguistics, 2024-03)
      [Abstract]: Depression is a global concern suffered by millions of people, significantly impacting their thoughts and behavior. Over the years, heightened awareness, spurred by health campaigns and other initiatives, has ...

    • 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 ...