Diego García-Gil

23 papers C 2Misc 1Journal 18Unranked 1
YearRankTypeTitle / Venue / Authors
2026 J jnl
Guest editorial: Mixture of experts and ensemble learning for big data.
Inf. Fusion
Mohammad Sultan Mahmud, Diego García-Gil, Joshua Zhexue Huang, Alladoumbaye Ngueilbaye, Xudong Sun
2025 J jnl
Benchmarking Anomaly Detection Methods: Insights From the UCR Time Series Anomaly Archive.
Expert Syst. J. Knowl. Eng.
Francisco J. Baldán, Diego García-Gil
2025 J jnl
Developing Big Data anomaly dynamic and static detection algorithms: AnomalyDSD spark package.
Inf. Sci.
Diego García-Gil, David López, Daniel Argüelles-Martino, Jacinto Carrasco, Ignacio Aguilera-Martos, Julián Luengo, Francisco Herrera
2025 J jnl
RSPCA: Random Sample Partition and Clustering Approximation for ensemble learning of big data.
Pattern Recognit.
Mohammad Sultan Mahmud, Hua Zheng, Diego García-Gil, Salvador García, Joshua Zhexue Huang
2025 J jnl
Revolutionizing Sperm Analysis with AI: A Review of Computer-Aided Sperm Analysis Systems.
Comput.
Francisco J. Baldán, Diego García-Gil, Carlos Fernandez-Basso
2025 J jnl
WinStat: A Family of Trainable Positional Encodings for Transformers in Time Series Forecasting.
Mach. Learn. Knowl. Extr.
Cristhian Moya-Mota, Ignacio Aguilera-Martos, Diego García-Gil, Julián Luengo
2024 — conf
Analysis of a Parallel and Distributed BPSO Algorithm for EEG Classification: Impact on Energy, Time and Accuracy.
IWBBIO (1)
Juan José Escobar, Jesús López-Rodríguez, Diego García-Gil, Roberto Morcillo-Jiménez, Beatriz Prieto, Andrés Ortiz, Dragi Kimovski
2024 J jnl
Smart Data Driven Decision Trees Ensemble Methodology for Imbalanced Big Data.
Cogn. Comput.
Diego García-Gil, Salvador García, Ning Xiong, Francisco Herrera
2023 J jnl
Fusing anomaly detection with false positive mitigation methodology for predictive maintenance under multivariate time series.
Inf. Fusion
David López, Ignacio Aguilera-Martos, Marta García-Bárzana, Francisco Herrera, Diego García-Gil, Julián Luengo
2023 J jnl
Multi-step histogram based outlier scores for unsupervised anomaly detection: ArcelorMittal engineering dataset case of study.
Neurocomputing
Ignacio Aguilera-Martos, Marta García-Bárzana, Diego García-Gil, Jacinto Carrasco, David López, Julián Luengo, Francisco Herrera
2021 J jnl
Anomaly detection in predictive maintenance: A new evaluation framework for temporal unsupervised anomaly detection algorithms.
Neurocomputing
Jacinto Carrasco, David López, Ignacio Aguilera-Martos, Diego García-Gil, Irina Markova, Marta García-Bárzana, Manuel Arias-Rodil, Julián Luengo, Francisco Herrera
2020 — book
Big Data Preprocessing - Enabling Smart Data
Julián Luengo, Diego García-Gil, Sergio Ramírez-Gallego, Salvador García, Francisco Herrera
2020 J jnl
Smart Data based Ensemble for Imbalanced Big Data Classification.
CoRR
Diego García-Gil, Johan Holmberg, Salvador García, Ning Xiong, Francisco Herrera
2019 C conf
A First Approach on Big Data Missing Values Imputation.
IoTBDS
Besay Montesdeoca, Julián Luengo, Jesús Maillo, Diego García-Gil, Salvador García, Francisco Herrera
2019 C conf
Big Data Preprocessing as the Bridge between Big Data and Smart Data: BigDaPSpark and BigDaPFlink Libraries.
IoTBDS
Diego García-Gil, Alejandro Alcalde-Barros, Julián Luengo, Salvador García, Francisco Herrera
2019 J jnl
Enabling Smart Data: Noise filtering in Big Data classification.
Inf. Sci.
Diego García-Gil, Julián Luengo, Salvador García, Francisco Herrera
2019 J jnl
From Big to Smart Data: Iterative ensemble filter for noise filtering in Big Data classification.
Int. J. Intell. Syst.
Diego García-Gil, Francisco Luque Sánchez, Julián Luengo, Salvador García, Francisco Herrera
2019 J jnl
Transforming big data into smart data: An insight on the use of the k-nearest neighbors algorithm to obtain quality data.
WIREs Data Mining Knowl. Discov.
Isaac Triguero, Diego García-Gil, Jesús Maillo, Julián Luengo, Salvador García, Francisco Herrera
2018 J jnl
DPASF: A Flink Library for Streaming Data preprocessing.
CoRR
Alejandro Alcalde-Barros, Diego García-Gil, Salvador García, Francisco Herrera
2018 J jnl
MRQAR: A generic MapReduce framework to discover quantitative association rules in big data problems.
Knowl. Based Syst.
Diana Martín, María Martínez-Ballesteros, Diego García-Gil, Jesús Alcalá-Fdez, Francisco Herrera, José Cristóbal Riquelme Santos
2018 Misc conf
On the Use of Random Discretization and Dimensionality Reduction in Ensembles for Big Data.
HAIS
Diego García-Gil, Sergio Ramírez-Gallego, Salvador García, Francisco Herrera
2018 J jnl
Principal Components Analysis Random Discretization Ensemble for Big Data.
Knowl. Based Syst.
Diego García-Gil, Sergio Ramírez-Gallego, Salvador García, Francisco Herrera
2017 J jnl
Enabling Smart Data: Noise filtering in Big Data classification.
CoRR
Diego García-Gil, Julián Luengo, Salvador García, Francisco Herrera