| 2025 | CBMS | Deep Learning Approaches to Assessing University Students' Health-Related Quality of Life: A Comparative Study of MLP and GNN. | Jos Luis vila-Jimnez, Manuel Rich-Ruiz, Francisco J. Rodrguez-Lozano, Vanesa Cantn-Habas, Sebastin Ventura |
| 2025 | DSAA | Enhancing Medical Diagnosis with Instance Hardness-Guided Multi-Level Cross-Validation for Imbalanced Learning. | Mabrouka Salmi, Dalia Atif, Sebastin Ventura |
| 2025 | IDEAL | MIHT: A Hoeffding Tree for Time Series Classification Using Multiple Instance Learning. | Aurora Esteban, Amelia Zafra, Sebastin Ventura |
| 2025 | IWANN | Modeling Student-Subject Interactions with GNNs for Grade Prediction. | Ghaidaa Ahmed Ali, Jos Luis vila-Jimnez, Mohammed Ibrahim Al-Twijri, Sebastin Ventura |
| 2023 | CAIP | A Comparison of Neural Network-Based Super-Resolution Models on 3D Rendered Images. | Rafael Berral-Soler, Francisco Jos Madrid-Cuevas, Sebastin Ventura, Rafael Muoz-Salinas, Manuel J. Marn-Jimnez |
| 2023 | CBMS | Radiomics Software Tools: A comparative Analysis on Breast Cancer. | Eduardo Almeda Luna, Jos Mara Luna, Sebastin Ventura |
| 2023 | HAIS | A Novel Genetic Algorithm with Specialized Genetic Operators for Clustering. | Hermes Robles-Berumen, Amelia Zafra, Sebastin Ventura |
| 2022 | CEC | Smart Operators for Inducing Colorectal Cancer Classification Trees with PonyGE2 Grammatical Evolution Python Package. | Jos A. Delgado-Osuna, Carlos Garca-Martnez, Sebastin Ventura |
| 2020 | CEC | A Preliminary Study on Evolutionary Clustering for Multiple Instance Learning. | Aurora Esteban, Amelia Zafra, Sebastin Ventura |
| 2020 | CEC | Tree-Shaped Ensemble of Multi-Label Classifiers using Grammar-Guided Genetic Programming. | Jose M. Moyano, Eva Lucrecia Gibaja Galindo, Krzysztof J. Cios, Sebastin Ventura |
| 2020 | ECAI | Generating Ensembles of Multi-Label Classifiers Using Cooperative Coevolutionary Algorithms. | Jose M. Moyano, Eva L. Gibaja, Krzysztof J. Cios, Sebastin Ventura |
| 2020 | IPMU | Fast Convergence of Competitive Spiking Neural Networks with Sample-Based Weight Initialization. | Paolo Gabriel Cachi, Sebastin Ventura, Krzysztof Jozef Cios |
| 2019 | CBMS | Obtaining Tractable and Interpretable Descriptions for Cases with Complications from a Colorectal Cancer Database. | Jos Antonio Delgado-Osuna, Carlos Garca-Martnez, Sebastin Ventura, Jose Gmez Barbadillo |
| 2019 | CBMS | MiNerDoc: a Semantically Enriched Text Mining System to Transform Clinical Text into Knowledge. | Carmen Luque, Jos Mara Luna, Sebastin Ventura |
| 2019 | CBMS | A Supervised Methodology for Analyzing Dysregulation in Splicing Machinery: An Application in Cancer Diagnosis. | Oscar Gabriel Reyes Pupo, Ral M. Luque, Justo Castao, Sebastin Ventura |
| 2019 | EDUCON | Discovering Students' Engagement Behaviors in Confidence-based Assessment. | Rabia Maqsood, Paolo Ceravolo, Sebastin Ventura |
| 2019 | ICCS | ARFF Data Source Library for Distributed Single/Multiple Instance, Single/Multiple Output Learning on Apache Spark. | Jorge Gonzalez-Lopez, Sebastin Ventura, Alberto Cano |
| 2017 | CEC | Multi-view semi-supervised learning using genetic programming interpretable classification rules. | Carlos Garca-Martnez, Sebastin Ventura |
| 2017 | CEC | An evolutionary algorithm for optimizing the target ordering in Ensemble of Regressor Chains. | Jose M. Moyano, Eva Lucrecia Gibaja Galindo, Sebastin Ventura |
| 2017 | CEC | An evolutionary algorithm for mining rare association rules: A Big Data approach. | Francisco Padillo, Jos Mara Luna, Sebastin Ventura |
| 2017 | CEC | On the effect of local search in the multi-objective evolutionary discovery of software architectures. | Aurora Ramrez, Jos Ral Romero, Sebastin Ventura |
| 2017 | TrustCom | Large-Scale Multi-label Ensemble Learning on Spark. | Jorge Gonzalez-Lopez, Alberto Cano, Sebastin Ventura |
| 2016 | HAIS | A Data Structure to Speed-Up Machine Learning Algorithms on Massive Datasets. | Francisco Padillo, Jos Mara Luna, Alberto Cano, Sebastin Ventura |
| 2016 | ISDA | Mining Perfectly Rare Itemsets on Big Data: An Approach Based on Apriori-Inverse and MapReduce. | Francisco Padillo, Jos Mara Luna, Sebastin Ventura |
| 2016 | ISDA | Memetic Algorithms for the Automatic Discovery of Software Architectures. | Aurora Ramrez, Rafael Barbudo, Jos Ral Romero, Sebastin Ventura |
| 2016 | TrustCom | Subgroup Discovery on Big Data: Exhaustive Methodologies Using Map-Reduce. | Francisco Padillo, Jos Mara Luna, Sebastin Ventura |
| 2015 | EPIA | Synthesis of In-Place Iterative Sorting Algorithms Using GP: A Comparison Between STGP, SFGP, G3P and GE. | David Pinheiro, Alberto Cano, Sebastin Ventura |
| 2015 | GECCO | An Extensible JCLEC-based Solution for the Implementation of Multi-Objective Evolutionary Algorithms. | Aurora Ramrez, Jos Ral Romero, Sebastin Ventura |
| 2015 | LAK | Discovering clues to avoid middle school failure at early stages. | Manuel ngel Jimnez-Gmez, Jos Mara Luna, Cristbal Romero, Sebastin Ventura |
| 2014 | EDM | Accepting or Rejecting Students_ Self-grading in their Final Marks by using Data Mining. | Javier Fuentes, Cristbal Romero, Carlos Garca-Martnez, Sebastin Ventura |
| 2014 | GECCO | GPU-parallel subtree interpreter for genetic programming. | Alberto Cano, Sebastin Ventura |
| 2014 | GECCO | On the performance of multiple objective evolutionary algorithms for software architecture discovery. | Aurora Ramrez, Jos Ral Romero, Sebastin Ventura |
| 2014 | HAIS | Classification Rule Mining with Iterated Greedy. | Juan A. Pedraza, Carlos Garca-Martnez, Alberto Cano, Sebastin Ventura |
| 2013 | EDM | A Moodle Block for Selecting, Visualizing and Mining Students' Usage Data. | Cristbal Romero, Cristobal Castro, Sebastin Ventura |
| 2013 | EDM | A meta-learning approach for recommending a subset of white-box classification algorithms for Moodle datasets. | Cristbal Romero, Juan Luis Olmo, Sebastin Ventura |
| 2013 | EUROGP | A Grammar-Guided Genetic Programming Algorithm for Multi-Label Classification. | Alberto Cano, Amelia Zafra, Eva Lucrecia Gibaja Galindo, Sebastin Ventura |
| 2013 | EUROGP | Discovering Subgroups by Means of Genetic Programming. | Jos Mara Luna, Jos Ral Romero, Cristbal Romero, Sebastin Ventura |
| 2013 | GECCO | A novel component identification approach using evolutionary programming. | Aurora Ramrez, Jos Ral Romero, Sebastin Ventura |
| 2012 | EDM | Classification via clustering for predicting final marks starting from the student participation in Forums. | Manuel Ignacio Lpez, Cristbal Romero, Sebastin Ventura, Jos Mara Luna |
| 2012 | EDM | Meta-learning Approach for Automatic Parameter Tuning: A case of study with educational datasets. | Mara De Mar Molina, Cristbal Romero, Sebastin Ventura, Jos Mara Luna |
| 2012 | EUROGP | Multi-Objective Ant Programming for Mining Classification Rules. | Juan Luis Olmo, Jos Ral Romero, Sebastin Ventura |
| 2012 | ISDA | VisualJCLEC: A visual framework for evolutionary computation. | Juan Ignacio Jaen, Jos Ral Romero, Sebastin Ventura |
| 2012 | ISDA | A genetic programming free-parameter algorithm for mining association rules. | Jos Mara Luna, Jos Ral Romero, Cristbal Romero, Sebastin Ventura |
| 2012 | ISDA | Binary and multiclass imbalanced classification using multi-objective ant programming. | Juan Luis Olmo, Alberto Cano, Jos Ral Romero, Sebastin Ventura |
| 2012 | ISDA | Learning similarity metric to improve the performance of lazy multi-label ranking algorithms. | Oscar Gabriel Reyes Pupo, Carlos Morell, Sebastin Ventura |
| 2011 | EDM | Predicting School Failure Using Data Mining. | Carlos Mrquez-Vera, Cristbal Romero, Sebastin Ventura |
| 2011 | EDM | A Java Desktop Tool for Mining Moodle Data. | Rafael Pedraza Perez, Cristbal Romero, Sebastin Ventura |
| 2011 | HAIS | JCLEC Meets WEKA! | Alberto Cano, Jos Mara Luna, Juan Luis Olmo, Sebastin Ventura |
| 2011 | HAIS | A Parallel Genetic Programming Algorithm for Classification. | Alberto Cano, Amelia Zafra, Sebastin Ventura |
| 2011 | ISDA | An EP algorithm for learning highly interpretable classifiers. | Alberto Cano, Amelia Zafra, Sebastin Ventura |
| 2011 | ISDA | Association rule mining using a multi-objective grammar-based ant programming algorithm. | Juan Luis Olmo, Jos Mara Luna, Jos Ral Romero, Sebastin Ventura |
| 2010 | CEC | G3PARM: A Grammar Guided Genetic Programming algorithm for mining association rules. | Jos Mara Luna, Jos Ral Romero, Sebastin Ventura |
| 2010 | CEC | A grammar based Ant Programming algorithm for mining classification rules. | Juan Luis Olmo, Jos Ral Romero, Sebastin Ventura |
| 2010 | EDM | Mining Rare Association Rules from e-Learning Data. | Cristbal Romero, Jos Ral Romero, Jos Mara Luna, Sebastin Ventura |
| 2010 | EDM | Class Association Rules Mining from Students' Test Data. | Cristbal Romero, Sebastin Ventura, Ekaterina Vasilyeva, Mykola Pechenizkiy |
| 2010 | GECCO | Grammar guided genetic programming for multiple instance learning: an experimental study. | Amelia Zafra, Sebastin Ventura |
| 2010 | HAIS | Evolving Multi-label Classification Rules with Gene Expression Programming: A Preliminary Study. | Jos Luis vila-Jimnez, Eva Lucrecia Gibaja Galindo, Sebastin Ventura |
| 2010 | HAIS | Solving Classification Problems Using Genetic Programming Algorithms on GPUs. | Alberto Cano, Amelia Zafra, Sebastin Ventura |
| 2010 | HAIS | Analysis of the Effectiveness of G3PARM Algorithm. | Jos Mara Luna, Jos Ral Romero, Sebastin Ventura |
| 2010 | HAIS | Reducing Dimensionality in Multiple Instance Learning with a Filter Method. | Amelia Zafra, Mykola Pechenizkiy, Sebastin Ventura |
| 2010 | ISDA | A TDIDT technique for multi-label classification. | Eva Lucrecia Gibaja Galindo, Manuel Victoriano, Jos Luis vila-Jimnez, Sebastin Ventura |
| 2010 | ISDA | An intruder detection approach based on infrequent rating pattern mining. | Jos Mara Luna, Aurora Ramrez, Jos Ral Romero, Sebastin Ventura |
| 2010 | ISDA | Feature selection is the ReliefF for multiple instance learning. | Amelia Zafra, Mykola Pechenizkiy, Sebastin Ventura |
| 2010 | PAAMS | An Automatic Programming ACO-Based Algorithm for Classification Rule Mining. | Juan Luis Olmo, Jos Mara Luna, Jos Ral Romero, Sebastin Ventura |
| 2009 | EDM | Collaborative Data Mining Tool for Education. | Cristbal Romero, Sebastin Ventura, Enrique Garca, Carlos de Castro, Miguel Gea |
| 2009 | EDM | Predicting Student Grades in Learning Management Systems with Multiple Instance Learning Genetic Programming. | Amelia Zafra, Sebastin Ventura |
| 2009 | HAIS | Multi-label Classification with Gene Expression Programming. | Jos Luis vila-Jimnez, Eva Lucrecia Gibaja Galindo, Sebastin Ventura |
| 2009 | HAIS | A Comparison of Multi-objective Grammar-Guided Genetic Programming Methods to Multiple Instance Learning. | Amelia Zafra, Sebastin Ventura |
| 2009 | IDEAL | A Niching Algorithm to Learn Discriminant Functions with Multi-Label Patterns. | Jos Luis vila-Jimnez, Eva Lucrecia Gibaja Galindo, Amelia Zafra, Sebastin Ventura |
| 2009 | ISDA | Predicting Academic Achievement Using Multiple Instance Genetic Programming. | Amelia Zafra, Cristbal Romero, Sebastin Ventura |
| 2008 | EDM | Mining and Visualizing Visited Trails in Web-Based Educational Systems. | Cristbal Romero, Sergio Gutirrez Santos, Manuel Freire, Sebastin Ventura |
| 2008 | EDM | Data Mining Algorithms to Classify Students. | Cristbal Romero, Sebastin Ventura, Pedro G. Espejo, Csar Hervs |
| 2008 | EDM | Analyzing Rule Evaluation Measures with Educational Datasets: A Framework to Help the Teacher. | Sebastin Ventura, Cristbal Romero, Csar Hervs |
| 2008 | HIS | Multiple Instance Learning with MultiObjective Genetic Programming for Web Mining. | Amelia Zafra, Eva Lucrecia Gibaja Galindo, Sebastin Ventura |
| 2007 | IWANN | Multiple Instance Learning with Genetic Programming for Web Mining. | Amelia Zafra, Sebastin Ventura, Enrique Herrera-Viedma, Cristbal Romero |
| 2006 | IDEAL | Using Rules Discovery for the Continuous Improvement of e-Learning Courses. | Enrique Garca, Cristbal Romero, Sebastin Ventura, Carlos de Castro |
| 2006 | IDEAL | Evolutionary Product-Unit Neural Networks for Classification. | Francisco J. Martnez-Estudillo, Csar Hervs-Martnez, Pedro Antonio Gutirrez Pea, Alfonso C. Martnez-Estudillo, Sebastin Ventura |
| 2001 | ESANN | A two steps method: non linear regression and pruning neural network for analyzing multicomponent mixtures. | Csar Hervs-Martnez, Jos Antonio Martinez Heras, Sebastin Ventura, Manuel Silva |