An Experimental Study on Combining Binarization Techniques and Ensemble Methods of Decision Trees. - Juan José Rodríguez Diez; José-Francisco Díez-Pastor; Álvar Arnaiz-González; César Ignacio García-Osorio (MCS, 2015)

Instance selection for regression by discretization. - Álvar Arnaiz-González; José-Francisco Díez-Pastor; Juan José Rodríguez Diez; César Ignacio García-Osorio (Expert Syst. Appl., 2016)

Instance selection for regression: Adapting DROP. - Álvar Arnaiz-González; José-Francisco Díez-Pastor; Juan José Rodríguez Diez; César Ignacio García-Osorio (Neurocomputing, 2016)

Fusion of instance selection methods in regression tasks. - Álvar Arnaiz-González; Marcin Blachnik; Miroslaw Kordos; César Ignacio García-Osorio (Inf. Fusion, 2016)

Instance selection of linear complexity for big data. - Álvar Arnaiz-González; José-Francisco Díez-Pastor; Juan José Rodríguez; César Ignacio García-Osorio (Knowl. Based Syst., 2016)

Random feature weights for regression trees. - Álvar Arnaiz-González; José-Francisco Díez-Pastor; César Ignacio García-Osorio; Juan José Rodríguez Diez (Prog. Artif. Intell., 2016)

MR-DIS - A Scalable Instance Selection Algorithm using MapReduce on Spark. - Álvar Arnaiz-González; Alejandro González-Rogel; Carlos López Nozal (ERCIM News, 2017)

MR-DIS: democratic instance selection for big data by MapReduce. - Álvar Arnaiz-González; Alejandro González-Rogel; José-Francisco Díez-Pastor; Carlos López Nozal (Prog. Artif. Intell., 2017)

Local sets for multi-label instance selection. - Álvar Arnaiz-González; José-Francisco Díez-Pastor; Juan José Rodríguez Diez; César García-Osorio (Appl. Soft Comput., 2018)

Seshat - a web-based educational resource for teaching the most common algorithms of lexical analysis. - Álvar Arnaiz-González; José-Francisco Díez-Pastor; Ismael Ramos-Pérez; César García-Osorio (Comput. Appl. Eng. Educ., 2018)

Study of data transformation techniques for adapting single-label prototype selection algorithms to multi-label learning. - Álvar Arnaiz-González; José-Francisco Díez-Pastor; Juan José Rodríguez Diez; César García-Osorio (Expert Syst. Appl., 2018)

A taxonomic look at instance-based stream classifiers. - Iain A. D. Gunn; Álvar Arnaiz-González; Ludmila I. Kuncheva (Neurocomputing, 2018)

Evolutionary prototype selection for multi-output regression. - Miroslaw Kordos; Álvar Arnaiz-González; César García-Osorio (Neurocomputing, 2019)

Instance selection improves geometric mean accuracy: a study on imbalanced data classification. - Ludmila I. Kuncheva; Álvar Arnaiz-González; José-Francisco Díez-Pastor; Iain A. D. Gunn (Prog. Artif. Intell., 2019)

Feature Selection from High-Dimensional Data with Very Low Sample Size: A Cautionary Tale. - Ludmila I. Kuncheva; Clare E. Matthews; Álvar Arnaiz-González; Juan José Rodríguez (CoRR, 2020)

An experimental evaluation of mixup regression forests. - Juan José Rodríguez; Mario Juez-Gil; Álvar Arnaiz-González; Ludmila I. Kuncheva (Expert Syst. Appl., 2020)

Random Balance ensembles for multiclass imbalance learning. - Juan José Rodríguez; José-Francisco Díez-Pastor; Álvar Arnaiz-González; Ludmila I. Kuncheva (Knowl. Based Syst., 2020)

Experimental evaluation of ensemble classifiers for imbalance in Big Data. - Mario Juez-Gil; Álvar Arnaiz-González; Juan José Rodríguez; César García-Osorio (Appl. Soft Comput., 2021)

Approx-SMOTE: Fast SMOTE for Big Data on Apache Spark. - Mario Juez-Gil; Álvar Arnaiz-González; Juan José Rodríguez; Carlos López Nozal; César García-Osorio (Neurocomputing, 2021)

Rotation Forest for Big Data. - Mario Juez-Gil; Álvar Arnaiz-González; Juan José Rodríguez Diez; Carlos López Nozal; César García-Osorio (Inf. Fusion, 2021)

When is resampling beneficial for feature selection with imbalanced wide data? - Ismael Ramos-Pérez; Álvar Arnaiz-González; Juan José Rodríguez; César García-Osorio (Expert Syst. Appl., 2022)

Rotation Forest for multi-target regression. - Juan José Rodríguez; Mario Juez-Gil; Carlos López Nozal; Álvar Arnaiz-González (Int. J. Mach. Learn. Cybern., 2022)

Correction to: Rotation Forest for multi-target regression. - Juan José Rodríguez; Mario Juez-Gil; Carlos López Nozal; Álvar Arnaiz-González (Int. J. Mach. Learn. Cybern., 2022)

Detection of Stress Stimuli in Learning Contexts of iVR Environments. - José Miguel Ramírez-Sanz; Helia Marina Peña-Alonso; Ana Serrano Mamolar; Álvar Arnaiz-González; Andrés Bustillo (XR (2), 2023)

Personalising the Training Process with Adaptive Virtual Reality: A Proposed Framework, Challenges, and Opportunities. - Gadea Lucas-Pérez; José Miguel Ramírez-Sanz; Ana Serrano Mamolar; Álvar Arnaiz-González; Andrés Bustillo (XR (1), 2024)

An Extensive Performance Comparison between Feature Reduction and Feature Selection Preprocessing Algorithms on Imbalanced Wide Data. - Ismael Ramos-Pérez; José Antonio Barbero-Aparicio; Antonio Canepa-Oneto; Álvar Arnaiz-González; Jesús Manuel Maudes Raedo (Inf., 2024)

Towards automatic phytolith classification using feature extraction and combination strategies. - José-Francisco Díez-Pastor; Pedro Latorre-Carmona; Álvar Arnaiz-González; Antonio Canepa-Oneto; Javier Ruiz-Pérez; Débora Zurro (Prog. Artif. Intell., 2024)

Correction: Towards automatic phytolith classification using feature extraction and combination strategies. - José-Francisco Díez-Pastor; Pedro Latorre-Carmona; Álvar Arnaiz-González; Antonio Canepa-Oneto; Javier Ruiz-Pérez; Débora Zurro (Prog. Artif. Intell., 2024)

Developing Human-Centered Intelligent Learning Systems: the application of CARAIX framework. - Miguel Portaz; Angeles Manjarrés Riesco; Olga C. Santos; Raúl Cabestrero; Pilar Quirós; Mar Hermosilla; David Puertas-Ramirez; Jesus Boticario; Gadea Lucas-Pérez; Ana Serrano Mamolar; Álvar Arnaiz-González; Miguel Arevalillo-Herráez; et al. (UMAP (Adjunct Publication), 2025)

Remote sensing colour image semantic segmentation of trails created by large herbivorous Mammals. - José-Francisco Díez-Pastor; Francisco Javier Gonzalez-Moya; Pedro Latorre-Carmona; Francisco Javier Perez-Barbería; Ludmila I. Kuncheva; Antonio Canepa-Oneto; Álvar Arnaiz-González; César García-Osorio (CoRR, 2025)