Viedma, D. T., Rivera Rivas, A. J., Charte Ojeda, F., & del Jesus Díaz, M. J. (2019). A First Approximation to the Effects of Classical Time Series Preprocessing Methods on LSTM Accuracy. 270-280. https://doi.org/10.1007/978-3-030-20521-8_23 (Original work published 2019)
Francisco Charte Ojeda
First name
Francisco
Last name
Charte Ojeda
2019
Martínez, F., Frías Bustamante, M. del P., Charte Ojeda, F., & Rivera Rivas, A. J. (2019). Time Series Forecasting with KNN in R: the tsfknn Package. The R Journal, 11, 229-242. https://doi.org/10.32614/RJ-2019-004 (Original work published 2019)
2018
Pulgar Rubio, F. J., Charte Ojeda, F., Rivera Rivas, A. J., & del Jesus Díaz, M. J. (2018). A First Approach to Face Dimensionality Reduction Through Denoising Autoencoders. 439-447. Madrid (Spain). https://doi.org/10.1007/978-3-030-03493-1_46 (Original work published)
Charte, D. ", Charte Ojeda, F., García López, S., del Jesus Díaz, M. J., & Herrera Triguero, F. (2018). A practical tutorial on autoencoders for nonlinear feature fusion: Taxonomy, models, software and guidelines. 949-950. Granada (Spain). (Original work published)
Charte, D. ", Charte Ojeda, F., García López, S., & Herrera Triguero, F. (2018). A snapshot on nonstandard supervised learning problems: taxonomy, relationships, problem transformations and algorithm adaptations. Progress in Artificial Intelligence. https://doi.org/10.1007/s13748-018-00167-7 (Original work published 2026)
Pulgar Rubio, F. J., Charte Ojeda, F., Rivera Rivas, A. J., & del Jesus Díaz, M. J. (2018). AEkNN: An AutoEncoder kNN-Based Classifier With Built-in Dimensionality Reduction. International Journal of Computational Intelligence Systems, 12, 436-452. https://doi.org/10.2991/ijcis.2019.0025 (Original work published 2018)
Trujillo, D., Rivera Rivas, A. J., Charte Ojeda, F., & del Jesus Díaz, M. J. (2018). An Approximation to Deep Learning Touristic-Related Time Series Forecasting. 448-456. Madrid (Spain). https://doi.org/10.1007/978-3-030-03493-1_47 (Original work published)
Pulgar Rubio, F. J., Rivera Rivas, A. J., Charte Ojeda, F., & del Jesus Díaz, M. J. (2018). Análisis del impacto de datos desbalanceados en el rendimiento predictivo de redes neuronales convolucionales. 1213-1218. Granada (Spain). (Original work published)
Rivera Rivas, A. J., Charte Ojeda, F., Espinilla, M., & Pérez Godoy, M. D. (2018). Nuevas arquitecturas hardware de procesamiento de alto rendimiento para aprendizaje profundo. Enseñanza Y Aprendizaje de Ingeniería de Computadores. Revista de Experiencias Docentes en Ingeniería de Computadores, 8, 67-83.
Charte Ojeda, F., Rivera Rivas, A. J., Charte, D. ", del Jesus Díaz, M. J., & Herrera Triguero, F. (2018). Tips, guidelines and tools for managing multi-label datasets: The mldr.datasets R package and the Cometa data repository. Neurocomputing, 289, 68-85. https://doi.org/10.1016/j.neucom.2018.02.011