Charte Ojeda, F. ., Rivera Rivas, A. J. ., Martínez, F. ., & del Jesus Díaz, M. J. . (2019). Automating Autoencoder Architecture Configuration: An Evolutionary Approach. 339-349. https://doi.org/10.1007/978-3-030-19591-5_35 (Original work published 2019)
Francisco Charte Ojeda
First name
Francisco
Last name
Charte Ojeda
2019
Charte Ojeda, F. ., Rivera Rivas, A. J. ., del Jesus Díaz, M. J. ., & Herrera Triguero, F. . (2019). Dealing with difficult minority labels in imbalanced mutilabel data sets. Neurocomputing, 326, 39-53. https://doi.org/10.1016/j.neucom.2016.08.158
2018
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
Viedma, D. T., Rivera Rivas, A. J. ., Charte Ojeda, F. ., & del Jesus Díaz, M. J. . (2018). Una primera aproximación a la predicción de variables turísticas con Deep Learning. 939-943. Granada (Spain). (Original work published)
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)