Publications
A practical tutorial on autoencoders for nonlinear feature fusion: Taxonomy, models, software and guidelines,
, XVIII Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA 2018), 10, Granada (Spain), p.949–950, (2018)
2018-CAEPIA-TutorialAEs.pdf (59.39 KB)

Análisis visual de técnicas no supervisadas de deep learning con el paquete dlvisR,
, XVII Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA 2016), 9, Salamanca (Spain), p.895–904, (2016)
2016-CAEPIA-dlvisR.pdf (2.56 MB)

mldr: Paquete R para Exploración de Datos Multietiqueta,
, XVI Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA 2015), 11, Albacete (Spain), p.695–704, (2015)
2015-CAEPIA-mldr.pdf (2.39 MB)

R Ultimate Multilabel Dataset Repository,
, 11th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2016, 4, Seville (Spain), p.487–499, (2016)
2016-HAIS-RUMDR.pdf (1.3 MB)

A snapshot on nonstandard supervised learning problems: taxonomy, relationships, problem transformations and algorithm adaptations,
, Progress in Artificial Intelligence, Nov, (2018)
A snapshot on nonstandard supervised learning problems: taxonomy, relationships, problem transformations and algorithm adaptations,
, Progress in Artificial Intelligence, 11, (In Press)
2018-PRAI-NonStandard-Accepted.pdf (951.61 KB)

Ruta: implementations of neural autoencoders in R,
, Knowledge-Based Systems, p.In press, (In Press)
Tips, guidelines and tools for managing multi-label datasets: The mldr.datasets R package and the Cometa data repository,
, Neurocomputing, Volume 289, p.68–85, (2018)
2018-Neucom-TipsMLCCometa-compressed.pdf (1017.86 KB)

Working with Multilabel Datasets in R: The mldr Package,
, The R Journal, Volume 7, Number 2, p.149–162, (2015)
2015-RJournal-mldr.pdf (1.16 MB)
