Enrique González Rodrigo

According to our database, Enrique González Rodrigo authored at least 9 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Efficient ensembles of distance-based label ranking trees.

Enrique González Rodrigo, Juan C. Alfaro, Juan A. Aledo, José A. Gámez

Expert Syst. J. Knowl. Eng., April, 2024

Label ranking oblique trees.

Enrique González Rodrigo, Juan C. Alfaro, Juan A. Aledo, José A. Gámez

Knowl. Based Syst., 2024

2021

Mixture-Based Probabilistic Graphical Models for the Label Ranking Problem.

Enrique González Rodrigo, Juan C. Alfaro, Juan A. Aledo, José A. Gámez

Entropy, 2021

2019

Machine learning from crowds: A systematic review of its applications.

Enrique González Rodrigo, Juan A. Aledo, José A. Gámez

WIREs Data Mining Knowl. Discov., 2019

Scaling up the learning-from-crowds GLAD algorithm using instance-difficulty clustering.

Enrique González Rodrigo, Juan A. Aledo, José A. Gámez

Prog. Artif. Intell., 2019

spark-crowd: A Spark Package for Learning from Crowdsourced Big Data.

Enrique González Rodrigo, Juan A. Aledo, José A. Gámez

J. Mach. Learn. Res., 2019

CiDAEN: An Online Data Science Course.

Luis de la Ossa, Pablo Bermejo, Juan A. Aledo, José A. Gámez, José Miguel Puerta, Cristina Romero-González, Jacinto Arias, Javier Cózar, Enrique González Rodrigo, Juan Ignacio Alonso-Barba, Jesus Martínez-Gómez

Proceedings of the Higher Education Learning Methodologies and Technologies Online, 2019

A Probabilistic Graphical Model-Based Approach for the Label Ranking Problem.

Juan Carlos Alfaro Jiménez, Enrique González Rodrigo, Juan A. Aledo, José Antonio Gámez

Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2019

2018

CGLAD: Using GLAD in Crowdsourced Large Datasets.

Enrique González Rodrigo, Juan A. Aledo, José A. Gámez

Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2018, 2018