Publications (93)

2023

  1. XAIRE: An ensemble-based methodology for determining the relative importance of variables in regression tasks. Application to a hospital emergency department

    Artificial Intelligence in Medicine, Vol. 137

2022

  1. Low-cost IoT gas concentrator system prototype

    15th International Conference of Technology, Learning and Teaching of Electronics, TAEE 2022 - Proceedings

  2. Reducing Data Complexity Using Autoencoders With Class-Informed Loss Functions

    IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 44, Núm. 12, pp. 9549-9560

  3. Strategies for time series forecasting with generalized regression neural networks

    Neurocomputing, Vol. 491, pp. 509-521

2021

  1. ClEnDAE: A classifier based on ensembles with built-in dimensionality reduction through denoising autoencoders

    Information Sciences, Vol. 565, pp. 146-176

  2. Slicer: Feature Learning for Class Separability with Least-Squares Support Vector Machine Loss and COVID-19 Chest X-Ray Case Study

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  3. Slicer: feature Learning for Class Separability with Least-Squares Support Vector Machine Loss and COVID-19 Chest X-Ray Case Study

    Hybrid Artificial Intelligent Systems: 16th International Conference, HAIS 2021. Bilbao, Spain. September 22–24, 2021. Proceedings

2020

  1. A Comprehensive and Didactic Review on Multilabel Learning Software Tools

    IEEE Access, Vol. 8, pp. 50330-50354

  2. An analysis on the use of autoencoders for representation learning: Fundamentals, learning task case studies, explainability and challenges

    Neurocomputing, Vol. 404, pp. 93-107

  3. Artificial intelligence within the interplay between natural and artificial computation: Advances in data science, trends and applications

    Neurocomputing, Vol. 410, pp. 237-270

  4. Choosing the proper autoencoder for feature fusion based on data complexity and classifiers: Analysis, tips and guidelines

    Information Fusion, Vol. 54, pp. 44-60

  5. E2PAMEA: A fast evolutionary algorithm for extracting fuzzy emerging patterns in big data environments

    Neurocomputing, Vol. 415, pp. 60-73

  6. El ecosistema de aprendizaje del estudiante universitario en la post-pandemia: metodologías y herramientas

    Enseñanza y aprendizaje de ingeniería de computadores: Revista de Experiencias Docentes en Ingeniería de Computadores, Núm. 10, pp. 15-38

  7. EvoAAA: An evolutionary methodology for automated neural autoencoder architecture search

    Integrated Computer-Aided Engineering

2019

  1. A Showcase of the Use of Autoencoders in Feature Learning Applications

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  2. A snapshot on nonstandard supervised learning problems: taxonomy, relationships, problem transformations and algorithm adaptations

    Progress in Artificial Intelligence, Vol. 8, Núm. 1

  3. Automatic Time Series Forecasting with GRNN: A Comparison with Other Models

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  4. Automating Autoencoder Architecture Configuration: An Evolutionary Approach

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  5. Dealing with difficult minority labels in imbalanced mutilabel data sets

    Neurocomputing, Vol. 326-327, pp. 39-53

  6. REMEDIAL-HwR: Tackling multilabel imbalance through label decoupling and data resampling hybridization

    Neurocomputing, Vol. 326-327, pp. 110-122