Publicaciones en las que colabora con MIGUEL DAMAS HERMOSO (35)

2021

  1. A lexicographic cooperative co-evolutionary approach for feature selection

    Neurocomputing, Vol. 463, pp. 59-76

  2. Energy-Time Profiling for Machine Learning Methods to EEG Classification

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

  3. Performance Study of Ant Colony Optimization for Feature Selection in EEG Classification

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

  4. Recurrent Neural Networks and Efficiency in High-Dimensional EEG Classification

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

2020

  1. A parallel and distributed multi-population GA with asynchronous migrations: Energy-time analysis for heterogeneous systems

    GECCO 2020 Companion - Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion

  2. Cost-Efficiency of Convolutional Neural Networks for High-Dimensional EEG Classification

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

  3. Deep learning for EEG-based motor imagery classification: Accuracy-cost trade-off

    PLoS ONE, Vol. 15, Núm. 6

2019

  1. A new multi-objective wrapper method for feature selection – Accuracy and stability analysis for BCI

    Neurocomputing, Vol. 333, pp. 407-418

  2. Annálisis Energía-Tiempo de Redes Neuronales Convolucionales Distribuidas en Clusters Heterogéneos para clasificación de EEGs

    Avances en Arquitectura y Tecnología de Computadores: Actas de Jornadas SARTECO, Cáceres, 18 a 20 de septiembre de 2019| (Servicio de Publicaciones), pp. 109-115

  3. Energy-Time Analysis of Convolutional Neural Networks Distributed on Heterogeneous Clusters for EEG Classification

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

  4. Energy-aware load balancing of parallel evolutionary algorithms with heavy fitness functions in heterogeneous CPU-GPU architectures

    Concurrency and Computation: Practice and Experience

  5. Many-Objective Cooperative Co-evolutionary Feature Selection: A Lexicographic Approach

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

  6. Time-energy analysis of multilevel parallelism in heterogeneous clusters: the case of EEG classification in BCI tasks

    Journal of Supercomputing, Vol. 75, Núm. 7, pp. 3397-3425

2018

  1. A power-performance perspective to multiobjective electroencephalogram feature selection on heterogeneous parallel platforms

    Journal of Computational Biology

  2. Multi-objective feature selection for EEG classification with multi-level parallelism on heterogeneous CPU-GPU clusters

    GECCO 2018 Companion - Proceedings of the 2018 Genetic and Evolutionary Computation Conference Companion

  3. Prediction of energy consumption in a NSGA-II-based evolutionary algorithm

    GECCO 2018 Companion - Proceedings of the 2018 Genetic and Evolutionary Computation Conference Companion

  4. Speedup and energy analysis of EEG classification for BCI tasks on CPU-GPU clusters

    ACM International Conference Proceeding Series

  5. Uso y difusión de la plataforma educativa SWAD / OpenSWAD en la Universidad de Granada y en el mundo

    Enseñanza y aprendizaje de ingeniería de computadores: Revista de Experiencias Docentes en Ingeniería de Computadores, Núm. 8, pp. 117-144

2017

  1. A parallel island approach to multiobjective feature selection for brain-computer interfaces

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 10305 LNCS, pp. 16-27

  2. Assessing Energy Consumption and Runtime Efficiency of Master- Worker Parallel Evolutionary Algorithms in CPU-GPU Systems

    Annals of Multicore and GPU Programming: AMGP, Vol. 4, Núm. 1, pp. 23-36