Publicaciones en las que colabora con Francisco Herrera Triguero (311)

2022

  1. 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

  2. Una visión actual de la inteligencia artificial: Recorrido histórico, datos y aprendizaje, confiabilidad y datos

    El derecho y la inteligencia artificial (Editorial Universidad de Granada), pp. 51-80

2021

  1. A Preliminary Analysis on Software Frameworks for the Development of Spiking Neural Networks

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

  2. A Preliminary Analysis on Software Frameworks for the Development of Spiking Neural Networks

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

  3. 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)

  4. 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

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. Consensus Building With Individual Consistency Control in Group Decision Making

    IEEE Transactions on Fuzzy Systems, Vol. 27, Núm. 2, pp. 319-332

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

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

  5. Evolutionary fuzzy systems for explainable artificial intelligence: Why, when, what for, and where to?

    IEEE Computational Intelligence Magazine, Vol. 14, Núm. 1, pp. 69-81

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

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

  7. Ruta: Implementations of neural autoencoders in R

    Knowledge-Based Systems, Vol. 174, pp. 4-8

  8. Smartdata: Data preprocessing to achieve smart data in R

    Neurocomputing, Vol. 360, pp. 1-13

2018

  1. A forecasting methodology for workload forecasting in cloud systems

    IEEE Transactions on Cloud Computing, Vol. 6, Núm. 4, pp. 929-941

  2. A practical tutorial on autoencoders for nonlinear feature fusion: Taxonomy, models, software and guidelines

    Information Fusion, Vol. 44, pp. 78-96

  3. A practical tutorial on autoencoders for nonlinear feature fusion: taxonomy, models, software and guidelines

    XVIII Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA 2018): avances en Inteligencia Artificial. 23-26 de octubre de 2018 Granada, España