JUAN JOSÉ
LÓPEZ ESCOBAR
Alumno/a tese / doutorado
![Foto de Miguel](/img/nophoto.png)
Miguel
Damas
Miguel Damas-rekin lankidetzan egindako argitalpenak (21)
2023
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A distributed and energy-efficient KNN for EEG classification with dynamic money-saving policy in heterogeneous clusters
Computing, Vol. 105, Núm. 11, pp. 2487-2510
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Energy-Aware KNN for EEG Classification: A Case Study in Heterogeneous Platforms
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
2022
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Ant colony optimization for feature selection via a filter-randomized search heuristic
GECCO 2022 Companion - Proceedings of the 2022 Genetic and Evolutionary Computation Conference
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Boosting the convergence of a GA-based wrapper for feature selection problems on high-dimensional data
GECCO 2022 Companion - Proceedings of the 2022 Genetic and Evolutionary Computation Conference
2021
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A lexicographic cooperative co-evolutionary approach for feature selection
Neurocomputing, Vol. 463, pp. 59-76
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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)
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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)
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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
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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
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Deep learning for EEG-based motor imagery classification: Accuracy-cost trade-off
PLoS ONE, Vol. 15, Núm. 6
2019
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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)
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Energy-aware load balancing of parallel evolutionary algorithms with heavy fitness functions in heterogeneous CPU-GPU architectures
Concurrency and Computation: Practice and Experience
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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
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A power-performance perspective to multiobjective electroencephalogram feature selection on heterogeneous parallel platforms
Journal of Computational Biology
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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
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Speedup and energy analysis of EEG classification for BCI tasks on CPU-GPU clusters
ACM International Conference Proceeding Series
2017
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Improving memory accesses for heterogeneous parallel multi-objective feature selection on eeg classification
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
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Issues on GPU parallel implementation of evolutionary high-dimensional multi-objective feature selection
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
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Parallel high-dimensional multi-objective feature selection for EEG classification with dynamic workload balancing on CPU–GPU architectures
Cluster Computing, Vol. 20, Núm. 3, pp. 1881-1897
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Power-performance evaluation of parallel multi-objective EEG feature selection on CPU-GPU platforms
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)