Now showing items 1-11 of 11

    • A review of green artificial intelligence: Towards a more sustainable future 

      Bolón-Canedo, Verónica; Morán-Fernández, Laura; Cancela, Brais; Alonso-Betanzos, Amparo (Elsevier B.V., 2024-09-28)
      [Abstract]: Green artificial intelligence (AI) is more environmentally friendly and inclusive than conventional AI, as it not only produces accurate results without increasing the computational cost but also ensures that ...
    • CUDA acceleration of MI-based feature selection methods 

      Beceiro, Bieito; González-Domínguez, Jorge; Morán-Fernández, Laura; Bolón-Canedo, Verónica; Touriño, Juan (Elsevier, 2024-08)
      [Abstract]: Feature selection algorithms are necessary nowadays for machine learning as they are capable of removing irrelevant and redundant information to reduce the dimensionality of the data and improve the quality of ...
    • Distributed classification based on distances between probability distributions in feature space 

      Montero Manso, Pablo; Morán-Fernández, Laura; Bolón-Canedo, Verónica; Vilar, José; Alonso-Betanzos, Amparo (Elsevier, 2019-09)
      [Abstract]: We consider a distributed framework where training and test samples drawn from the same distribution are available, with the training instances spread across disjoint nodes. In this setting, a novel learning ...
    • Do all roads lead to Rome? Studying distance measures in the context of machine learning 

      Blanco Mallo, Eva; Morán-Fernández, Laura; Remeseiro, Beatriz; Bolón-Canedo, Verónica (Elsevier Ltd, 2023-09)
      [Abstract]: Many machine learning and data mining tasks are based on distance measures, so a large amount of literature addresses this aspect somehow. Due to the broad scope of the topic, this paper aims to provide an ...
    • Feature selection for domain adaptation using complexity measures and swarm intelligence 

      Castillo-García, G.; Morán-Fernández, Laura; Bolón-Canedo, Verónica (Elsevier B.V., 2023-09-01)
      [Abstract]: Particle Swarm Optimization is an optimization algorithm that mimics the behaviour of a flock of birds, setting multiple particles that explore the search space guided by a fitness function in order to find the ...
    • Feature selection with limited bit depth mutual information for portable embedded systems 

      Morán-Fernández, Laura; Sechidis, Konstantinos; Bolón-Canedo, Verónica; Alonso-Betanzos, Amparo; Brown, Gavin (Elsevier, 2020-06)
      [Abstract]: Since wearable computing systems have grown in importance in the last years, there is an increased interest in implementing machine learning algorithms with reduced precision parameters/computations. Not only ...
    • Finding a needle in a haystack: insights on feature selection for classification tasks 

      Morán-Fernández, Laura; Bolón-Canedo, Verónica (Springer, 2024-04)
      [Abstract]: The growth of Big Data has resulted in an overwhelming increase in the volume of data available, including the number of features. Feature selection, the process of selecting relevant features and discarding ...
    • How Important Is Data Quality? Best Classifiers vs Best Features 

      Morán-Fernández, Laura; Bolón-Canedo, Verónica; Alonso-Betanzos, Amparo (Elsevier, 2021)
      [Abstract] The task of choosing the appropriate classifier for a given scenario is not an easy-to-solve question. First, there is an increasingly high number of algorithms available belonging to different families. And ...
    • Low-Precision Feature Selection on Microarray Data: An Information Theoretic Approach 

      Morán-Fernández, Laura; Bolón-Canedo, Verónica; Alonso-Betanzos, Amparo (Springer, 2022)
      [Abstract] The number of interconnected devices, such as personal wearables, cars, and smart-homes, surrounding us every day has recently increased. The Internet of Things devices monitor many processes, and have the ...
    • Reduced precision discretization based on information theory 

      Ares, Brais; Morán-Fernández, Laura; Bolón-Canedo, Verónica (Elsevier, 2022-01)
      [Abstract] In recent years, new technological areas have emerged and proliferated, such as the Internet of Things or embedded systems in drones, which are usually characterized by making use of devices with strict requirements ...
    • Towards federated feature selection: Logarithmic division for resource-conscious methods 

      Suárez-Marcote, Samuel; Morán-Fernández, Laura; Bolón-Canedo, Verónica (Elsevier, 2024)
      [Abstract]: Feature selection is a popular preprocessing step to reduce the dimensionality of the data while preserving the important information. In this paper, we propose an efficient and green feature selection method ...