CGLAD: Using GLAD in Crowdsourced Large Datasets. - Enrique González Rodrigo; Juan A. Aledo; José A. Gámez 001 (IDEAL (1), 2018)

A Probabilistic Graphical Model-Based Approach for the Label Ranking Problem. - Juan Carlos Alfaro Jiménez; Enrique González Rodrigo; Juan A. Aledo; José Antonio Gámez (ECSQARU, 2019)

CiDAEN: An Online Data Science Course. - Luis de la Ossa; Pablo Bermejo 001; Juan A. Aledo; José A. Gámez 001; José M. Puerta; Cristina Romero-González; Jacinto Arias; Javier Cózar; Enrique González Rodrigo; Juan Ignacio Alonso-Barba; Jesus Martínez-Gómez (HELMeTO, 2019)

spark-crowd: A Spark Package for Learning from Crowdsourced Big Data. - Enrique González Rodrigo; Juan A. Aledo; José A. Gámez 001 (J. Mach. Learn. Res., 2019)

Scaling up the learning-from-crowds GLAD algorithm using instance-difficulty clustering. - Enrique González Rodrigo; Juan A. Aledo; José A. Gámez 001 (Prog. Artif. Intell., 2019)

Machine learning from crowds: A systematic review of its applications. - Enrique González Rodrigo; Juan A. Aledo; José A. Gámez 001 (WIREs Data Mining Knowl. Discov., 2019)

Mixture-Based Probabilistic Graphical Models for the Label Ranking Problem. - Enrique González Rodrigo; Juan C. Alfaro; Juan A. Aledo; José A. Gámez 001 (Entropy, 2021)

Label ranking oblique trees. - Enrique González Rodrigo; Juan C. Alfaro; Juan A. Aledo; José A. Gámez 001 (Knowl. Based Syst., 2024)

Efficient ensembles of distance-based label ranking trees. - Enrique González Rodrigo; Juan C. Alfaro; Juan A. Aledo; José A. Gámez 001 (Expert Syst. J. Knowl. Eng., 2024)