| 2024 | IJCNN | Local Attention: Enhancing the Transformer Architecture for Efficient Time Series Forecasting. | Ignacio Aguilera-Martos, Andrs Herrera-Poyatos, Julin Luengo, Francisco Herrera |
| 2023 | HAIS | Revisiting Histogram Based Outlier Scores: Strengths and Weaknesses. | Ignacio Aguilera-Martos, Julin Luengo, Francisco Herrera |
| 2023 | HAIS | Optimizing LIME Explanations Using REVEL Metrics. | Ivn Sevillano-Garca, Julin Luengo, Francisco Herrera |
| 2020 | GECCO | Improving constrained clustering via decomposition-based multiobjective optimization with memetic elitism. | Germn Gonzlez-Almagro, Alejandro Rosales-Prez, Julin Luengo, Jos Ramn Cano, Salvador Garca |
| 2020 | HAIS | Agglomerative Constrained Clustering Through Similarity and Distance Recalculation. | Germn Gonzlez-Almagro, Juan-Luis Surez, Julin Luengo, Jos Ramn Cano, Salvador Garca |
| 2017 | HAIS | A Study on the Noise Label Influence in Boosting Algorithms: AdaBoost, GBM and XGBoost. | Anabel Gmez-Ros, Julin Luengo, Francisco Herrera |
| 2016 | HAIS | A First Study on the Use of Boosting for Class Noise Reparation. | Pablo Morales-Alvarez, Julin Luengo, Francisco Herrera |
| 2015 | ICPRAM | Naive Bayes Classifier with Mixtures of Polynomials. | Julin Luengo, Rafael Rum |
| 2014 | HAIS | Improving the Behavior of the Nearest Neighbor Classifier against Noisy Data with Feature Weighting Schemes. | Jos A. Sez, Joaqun Derrac, Julin Luengo, Francisco Herrera |
| 2014 | IDEAL | Managing Borderline and Noisy Examples in Imbalanced Classification by Combining SMOTE with Ensemble Filtering. | Jos A. Sez, Julin Luengo, Jerzy Stefanowski, Francisco Herrera |
| 2013 | HAIS | An Experimental Case of Study on the Behavior of Multiple Classifier Systems with Class Noise Datasets. | Jos A. Sez, Mikel Galar, Julin Luengo, Francisco Herrera |
| 2012 | HAIS | A First Study on Decomposition Strategies with Data with Class Noise Using Decision Trees. | Jos A. Sez, Mikel Galar, Julin Luengo, Francisco Herrera |
| 2012 | ICPRAM | A Preliminary Study on Selecting the Optimal Cut Points in Discretization by Evolutionary Algorithms. | Salvador Garca, Victoria Lpez, Julin Luengo, Cristbal J. Carmona, Francisco Herrera |
| 2011 | ISDA | Fuzzy Rule Based Classification Systems versus crisp robust learners trained in presence of class noise's effects: A case of study. | Jos A. Sez, Julin Luengo, Francisco Herrera |
| 2010 | ISKE | A first study on the noise impact in classes for Fuzzy Rule Based Classification Systems. | Jos A. Sez, Julin Luengo, Francisco Herrera |
| 2009 | EUSFLAT | On the use of Measures of Separability of Classes to Characterise the Domains of Competence of a Fuzzy Rule Based Classification System. | Julin Luengo, Francisco Herrera |
| 2009 | IDEAL | Implementation and Integration of Algorithms into the KEEL Data-Mining Software Tool. | Alberto Fernndez, Julin Luengo, Joaqun Derrac, Jess Alcal-Fdez, Francisco Herrera |
| 2009 | ISDA | A First Approach to Nearest Hyperrectangle Selection by Evolutionary Algorithms. | Salvador Garca, Joaqun Derrac, Julin Luengo, Francisco Herrera |
| 2009 | ISDA | Addressing Data-Complexity for Imbalanced Data-Sets: A Preliminary Study on the Use of Preprocessing for C4.5. | Julin Luengo, Alberto Fernndez, Salvador Garca, Francisco Herrera |
| 2009 | IWANN | Domains of Competence of Artificial Neural Networks Using Measures of Separability of Classes. | Julin Luengo, Francisco Herrera |
| 2007 | IWANN | A Study on the Use of Statistical Tests for Experimentation with Neural Networks. | Julin Luengo, Salvador Garca, Francisco Herrera |