• Case Study of Anomaly Detection and Quality Control of Energy Efficiency and Hygrothermal Comfort in Buildings 

      Eiras-Franco, Carlos; Flores, Miguel; Bolón-Canedo, Verónica; Zaragoza, Sonia; Fernández-Casal, Rubén; Naya, Salvador; Tarrío-Saavedra, Javier (2019)
      [Abstract] The aim of this work is to propose different statistical and machine learning methodologies for identifying anomalies and control the quality of energy efficiency and hygrothermal comfort in buildings. ...
    • Feature Selection in Big Image Datasets 

      Figueira-Domínguez, J. Guzmán; Bolón-Canedo, Verónica; Remeseiro, Beatriz (MDPI AG, 2020-08-24)
      [Abstract] In computer vision, current feature extraction techniques generate high dimensional data. Both convolutional neural networks and traditional approaches like keypoint detectors are used as extractors of high-level ...
    • Feature Selection With Limited Bit Depth Mutual Information for Embedded Systems 

      Morán-Fernández, Laura; Bolón-Canedo, Verónica; Alonso-Betanzos, Amparo (MDPI AG, 2018-09-17)
      [Abstract] Data is growing at an unprecedented pace. With the variety, speed and volume of data flowing through networks and databases, newer approaches based on machine learning are required. But what is really big in Big ...
    • GenEs: una plataforma para la generación, realización y evaluación de exámenes 

      Cabrero-Canosa, Mariano; Acha Aller, Santiago X. (Thomson-Paraninfo, 2006)
      Este artículo describe una herramienta de entorno web que asiste al profesor en la tarea completa de la evaluación: desde la fase de composición del examen, seleccionando aleatoriamente un conjunto representativo de ...
    • Improving Medical Data Annotation Including Humans in the Machine Learning Loop 

      Bobes-Bascarán, José; Mosqueira-Rey, E.; Alonso Ríos, David (MDPI, 2021)
      [Abstract] At present, the great majority of Artificial Intelligence (AI) systems require the participation of humans in their development, tuning, and maintenance. Particularly, Machine Learning (ML) systems could greatly ...
    • Integrating Iterative Machine Teaching and Active Learning into the Machine Learning Loop 

      Mosqueira-Rey, E.; Alonso Ríos, David; Baamonde-Lozano, Andrés (Elsevier, 2021)
      [Abstract] Scholars and practitioners are defining new types of interactions between humans and machine learning algorithms that we can group under the umbrella term of Human-in-the-Loop Machine Learning (HITL-ML). This ...
    • Interpretable market segmentation on high dimension data 

      Eiras-Franco, Carlos; Guijarro-Berdiñas, Bertha; Alonso-Betanzos, Amparo; Bahamonde, Antonio (M D P I AG, 2018-09-17)
      [Abstract] Obtaining relevant information from the vast amount of data generated by interactions in a market or, in general, from a dyadic dataset, is a broad problem of great interest both for industry and academia. Also, ...
    • On the Effectiveness of Convolutional Autoencoders on Image-Based Personalized Recommender Systems 

      Blanco, Eva; Remeseiro, Beatriz; Bolón-Canedo, Verónica; Alonso-Betanzos, Amparo (MDPI AG, 2020-08-19)
      [Abstract] Over the years, the success of recommender systems has become remarkable. Due to the massive arrival of options that a consumer can have at his/her reach, a collaborative environment was generated, where users ...
    • Quantum Factory Method: A Software Engineering Approach to Deal with Incompatibilities in Quantum Libraries 

      Magaz Romero, Samuel; Mosqueira-Rey, E.; Alvarez-Estevez, Diego; Moret-Bonillo, Vicente (Springer Nature, 2023-06)
      [Abstract]: The current context of Quantum Computing and its available technologies present an extensive variety of tools and lack of methodologies, leading to incompatibilities across platforms, which end up as inconsistencies ...
    • Regression Tree Based Explanation for Anomaly Detection Algorithm 

      López-Riobóo Botana, Iñigo Luis; Eiras-Franco, Carlos; Alonso-Betanzos, Amparo (MDPI AG, 2020-08-18)
      [Abstract] This work presents EADMNC (Explainable Anomaly Detection on Mixed Numerical and Categorical spaces), a novel approach to address explanation using an anomaly detection algorithm, ADMNC, which provides accurate ...
    • Sustainable personalisation and explainability in Dyadic Data Systems 

      Paz Ruza, Jorge; Eiras-Franco, Carlos; Guijarro-Berdiñas, Bertha; Alonso-Betanzos, Amparo (2022)
      [Abstract]: Systems that rely on dyadic data, which relate entities of two types together, have become ubiquitously used in fields such as media services, tourism business, e-commerce, and others. However, these systems ...
    • Usability Heuristics for Domain-Specific Languages (DSLs) 

      Mosqueira-Rey, E.; Alonso Ríos, David (ACM, 2020-03-30)
      [Abstract] The usability of Domain-Specific Languages (DSLs) has been attracting considerable interest from researchers lately. In particular, our literature review found many usability studies that make use of subjective ...