Publications

An analysis on the use of autoencoders for representation learning: Fundamentals, learning task case studies, explainability and challenges, Charte, David, Charte Francisco, del Jesus M. J., and Herrera F. , Neurocomputing, Volume 404, p.93-107, (2020)

• Google Scholar
• BibTeX

1-s2.0-S092523122030624X-main.pdf (0 bytes)

Artificial intelligence within the interplay between natural and artificial computation: Advances in data science, trends and applications, M.Górriz, Juan, Ramírez Javier, Ortíz Andrés, Martínez-Murcia Francisco J., Segovia Fermín, Suckling John, Leming Matthew, Zhang Yu-Dong, Álvarez-Sánchez José Ramón, Bologna Guido, et al. , Neurocomputing, Volume 410, p.237-270, (2020)

• Google Scholar
• BibTeX

A snapshot on nonstandard supervised learning problems: taxonomy, relationships, problem transformations and algorithm adaptations, Charte, David, Charte Francisco, García S., and Herrera F. , Progress in Artificial Intelligence, 11, Volume 8, p.1-14, (2019)

• Google Scholar
• BibTeX

2018-PRAI-NonStandard-Accepted.pdf (951.61 KB)

Ruta: implementations of neural autoencoders in R, Charte, David, Herrera F., and Charte Francisco , Knowledge-Based Systems, 06/2019, Volume 174, p.4-8, (2019)

• Google Scholar
• BibTeX

1-s2.0-S0950705119300140-main.pdf (421.73 KB)

A practical tutorial on autoencoders for nonlinear feature fusion: Taxonomy, models, software and guidelines, Charte, David, Charte Francisco, García S., del Jesus M. J., and Herrera F. , XVIII Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA 2018), 10, Granada (Spain), p.949–950, (2018)

• Google Scholar
• BibTeX

2018-CAEPIA-TutorialAEs.pdf (59.39 KB)

A snapshot on nonstandard supervised learning problems: taxonomy, relationships, problem transformations and algorithm adaptations, Charte, David, Charte Francisco, García S., and Herrera F. , Progress in Artificial Intelligence, Nov, (2018)

• Google Scholar
• BibTeX

Tips, guidelines and tools for managing multi-label datasets: The mldr.datasets R package and the Cometa data repository, Charte, Francisco, Rivera-Rivas A.J., Charte David, del Jesus M. J., and Herrera F. , Neurocomputing, Volume 289, p.68–85, (2018)

• Google Scholar
• BibTeX

2018-Neucom-TipsMLCCometa-compressed.pdf (1017.86 KB)

Análisis visual de técnicas no supervisadas de deep learning con el paquete dlvisR, Charte, David, Charte Francisco, and Herrera F. , XVII Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA 2016), 9, Salamanca (Spain), p.895–904, (2016)

• Google Scholar
• BibTeX

2016-CAEPIA-dlvisR.pdf (2.56 MB)

R Ultimate Multilabel Dataset Repository, Charte, Francisco, Charte David, Rivera-Rivas A.J., del Jesus M. J., and Herrera F. , 11th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2016, 4, Seville (Spain), p.487–499, (2016)

• Google Scholar
• BibTeX

RUMDR.pdf (294.87 KB)

mldr: Paquete R para Exploración de Datos Multietiqueta, Charte, David, and Charte Francisco , XVI Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA 2015), 11, Albacete (Spain), p.695–704, (2015)

• Google Scholar
• BibTeX

2015-CAEPIA-mldr.pdf (2.39 MB)

Working with Multilabel Datasets in R: The mldr Package, Charte, Francisco, and Charte David , The R Journal, Volume 7, Number 2, p.149–162, (2015)

• Google Scholar
• BibTeX

2015-RJournal-mldr.pdf (1.16 MB)