Computational Neural Networks in Conjunction with Principal Component Analysis for Resolving Highly Nonlinear Kinetics. - Sebastián Ventura; Manuel Silva 002; Dolores Pérez-Bendito; César Hervás (J. Chem. Inf. Comput. Sci., 1997)

Estimation of Parameters of Kinetic Compartmental Models by Use of Computational Neural Networks. - Sebastián Ventura; Manuel Silva 002; Dolores Pérez-Bendito; César Hervás (J. Chem. Inf. Comput. Sci., 1997)

Reconocimiento de funciones de producción láctea mediante redes neuronales podadas y entrenadas con un algoritmo genético. - César Hervás; Sebastián Ventura; J. Martínez (Inteligencia Artif., 1998)

Computational Neural Networks for Resolving Nonlinear Multicomponent Systems Based on Chemiluminescence Methods. - César Hervás; Sebastián Ventura; Manuel Silva 002; Dolores Pérez-Bendito (J. Chem. Inf. Comput. Sci., 1998)

A two steps method: non linear regression and pruning neural network for analyzing multicomponent mixtures. - César Hervás-Martínez; José Antonio Martinez Heras; Sebastián Ventura; Manuel Silva 002 (ESANN, 2001)

Application of Crossover Operators Based on Confidence Interval in Modeling Problems Using Real-Coding Genetic Algorithms. - Rafael del Castillo Gomariz; César Hervás-Martínez; Sebastián Ventura; Domingo Ortiz-Boyer (CAEPIA, 2003)

Discovering Prediction Rules in AHA! Courses. - Cristóbal Romero 001; Sebastián Ventura; Paul De Bra; Carlos de Castro (User Modeling, 2003)

Knowledge Discovery with Genetic Programming for Providing Feedback to Courseware Authors. - Cristóbal Romero 001; Sebastián Ventura; Paul De Bra (User Model. User Adapt. Interact., 2004)

An Authoring Tool for Building Both Mobile Adaptable Tests and Web-Based Adaptive or Classic Tests. - Cristóbal Romero 001; Sebastián Ventura; César Hervás-Martínez; Paul De Bra (AH, 2006)

Using Rules Discovery for the Continuous Improvement of e-Learning Courses. - Enrique García; Cristóbal Romero 001; Sebastián Ventura; Carlos de Castro (IDEAL, 2006)

Evolutionary Product-Unit Neural Networks for Classification. - Francisco J. Martínez-Estudillo; César Hervás-Martínez; Pedro Antonio Gutiérrez Peña; Alfonso C. Martínez-Estudillo; Sebastián Ventura (IDEAL, 2006)

Selection of Logical Operators for Inducing Comprehensible Knowledge. - Pedro G. Espejo; César Hervás; Sebastián Ventura; Cristóbal Romero 001 (Inteligencia Artif., 2006)

Web-based adaptive training simulator system for cardiac life support. - Cristóbal Romero 001; Sebastián Ventura; Eva Lucrecia Gibaja Galindo; César Hervás-Martínez; Francisco Romero Morales (Artif. Intell. Medicine, 2006)

Multi-objective Genetic Programming for Multiple Instance Learning. - Amelia Zafra; Sebastián Ventura (ECML, 2007)

Personalized Links Recommendation Based on Data Mining in Adaptive Educational Hypermedia Systems. - Cristóbal Romero 001; Sebastián Ventura; Jose Antonio Delgado; Paul De Bra (EC-TEL, 2007)

Multiple Instance Learning with Genetic Programming for Web Mining. - Amelia Zafra; Sebastián Ventura; Enrique Herrera-Viedma; Cristóbal Romero 001 (IWANN, 2007)

Educational data mining: A survey from 1995 to 2005. - Cristóbal Romero 001; Sebastián Ventura (Expert Syst. Appl., 2007)

Mining and Visualizing Visited Trails in Web-Based Educational Systems. - Cristóbal Romero 001; Sergio Gutiérrez Santos; Manuel Freire 001; Sebastián Ventura (EDM, 2008)

Data Mining Algorithms to Classify Students. - Cristóbal Romero 001; Sebastián Ventura; Pedro G. Espejo; César Hervás (EDM, 2008)

Analyzing Rule Evaluation Measures with Educational Datasets: A Framework to Help the Teacher. - Sebastián Ventura; Cristóbal Romero 001; César Hervás (EDM, 2008)

Multiple Instance Learning with MultiObjective Genetic Programming for Web Mining. - Amelia Zafra; Eva Lucrecia Gibaja Galindo; Sebastián Ventura (HIS, 2008)

Data mining in course management systems: Moodle case study and tutorial. - Cristóbal Romero 001; Sebastián Ventura; Enrique García (Comput. Educ., 2008)

Sistema recomendador colaborativo usando minería de datos distribuida para la mejora continua de cursos e-learning. - Enrique García Salcines; Cristóbal Romero 001; Sebastián Ventura; Carlos de-Castro-Lozano (Rev. Iberoam. de Tecnol. del Aprendiz., 2008)

JCLEC: a Java framework for evolutionary computation. - Sebastián Ventura; Cristóbal Romero 001; Amelia Zafra; Jose Antonio Delgado; César Hervás (Soft Comput., 2008)

Collaborative Data Mining Tool for Education. - Cristóbal Romero 001; Sebastián Ventura; Enrique García; Carlos de Castro; Miguel Gea (EDM, 2009)

Predicting Student Grades in Learning Management Systems with Multiple Instance Learning Genetic Programming. - Amelia Zafra; Sebastián Ventura (EDM, 2009)

Multi-label Classification with Gene Expression Programming. - José Luis Ávila-Jiménez; Eva Lucrecia Gibaja Galindo; Sebastián Ventura (HAIS, 2009)

A Comparison of Multi-objective Grammar-Guided Genetic Programming Methods to Multiple Instance Learning. - Amelia Zafra; Sebastián Ventura (HAIS, 2009)

A Niching Algorithm to Learn Discriminant Functions with Multi-Label Patterns. - José Luis Ávila-Jiménez; Eva Lucrecia Gibaja Galindo; Amelia Zafra; Sebastián Ventura (IDEAL, 2009)

Predicting Academic Achievement Using Multiple Instance Genetic Programming. - Amelia Zafra; Cristóbal Romero 001; Sebastián Ventura (ISDA, 2009)

Evaluating Web Based Instructional Models Using Association Rule Mining. - Enrique García; Cristóbal Romero 001; Sebastián Ventura; Carlos de Castro (UMAP, 2009)

Using mobile and web-based computerized tests to evaluate university students. - Cristóbal Romero 001; Sebastián Ventura; Paul De Bra (Comput. Appl. Eng. Educ., 2009)

Applying Web usage mining for personalizing hyperlinks in Web-based adaptive educational systems. - Cristóbal Romero 001; Sebastián Ventura; Amelia Zafra; Paul De Bra (Comput. Educ., 2009)

Evolutionary algorithms for subgroup discovery in e-learning: A practical application using Moodle data. - Cristóbal Romero 001; Pedro González 001; Sebastián Ventura; María José del Jesus; Francisco Herrera (Expert Syst. Appl., 2009)

Multi-instance genetic programming for web index recommendation. - Amelia Zafra; Cristóbal Romero 001; Sebastián Ventura; Enrique Herrera-Viedma (Expert Syst. Appl., 2009)

KEEL: a software tool to assess evolutionary algorithms for data mining problems. - Jesús Alcalá-Fdez; Luciano Sánchez; Salvador García 001; María José del Jesus; Sebastián Ventura; Josep Maria Garrell i Guiu; José Otero; Cristóbal Romero 001; Jaume Bacardit; Víctor M. Rivas; Juan Carlos Fernández 001; Francisco Herrera (Soft Comput., 2009)

An architecture for making recommendations to courseware authors using association rule mining and collaborative filtering. - Enrique García; Cristóbal Romero 001; Sebastián Ventura; Carlos de Castro (User Model. User Adapt. Interact., 2009)

G3PARM: A Grammar Guided Genetic Programming algorithm for mining association rules. - José María Luna; José Raúl Romero; Sebastián Ventura (IEEE Congress on Evolutionary Computation, 2010)

A grammar based Ant Programming algorithm for mining classification rules. - Juan Luis Olmo; José Raúl Romero; Sebastián Ventura (IEEE Congress on Evolutionary Computation, 2010)

Mining Rare Association Rules from e-Learning Data. - Cristóbal Romero 001; José Raúl Romero; José María Luna; Sebastián Ventura (EDM, 2010)

Class Association Rules Mining from Students' Test Data. - Cristóbal Romero 001; Sebastián Ventura; Ekaterina Vasilyeva; Mykola Pechenizkiy (EDM, 2010)

Grammar guided genetic programming for multiple instance learning: an experimental study. - Amelia Zafra; Sebastián Ventura (GECCO, 2010)

Evolving Multi-label Classification Rules with Gene Expression Programming: A Preliminary Study. - José Luis Ávila-Jiménez; Eva Lucrecia Gibaja Galindo; Sebastián Ventura (HAIS (2), 2010)

Solving Classification Problems Using Genetic Programming Algorithms on GPUs. - Alberto Cano 001; Amelia Zafra; Sebastián Ventura (HAIS (2), 2010)

Analysis of the Effectiveness of G3PARM Algorithm. - José María Luna; José Raúl Romero; Sebastián Ventura (HAIS (2), 2010)

Reducing Dimensionality in Multiple Instance Learning with a Filter Method. - Amelia Zafra; Mykola Pechenizkiy; Sebastián Ventura (HAIS (2), 2010)

Web Usage Mining for Improving Students Performance in Learning Management Systems. - Amelia Zafra; Sebastián Ventura (IEA/AIE (3), 2010)

A TDIDT technique for multi-label classification. - Eva Lucrecia Gibaja Galindo; Manuel Victoriano; José Luis Ávila-Jiménez; Sebastián Ventura (ISDA, 2010)

An intruder detection approach based on infrequent rating pattern mining. - José María Luna; Aurora Ramírez 001; José Raúl Romero; Sebastián Ventura (ISDA, 2010)

Feature selection is the ReliefF for multiple instance learning. - Amelia Zafra; Mykola Pechenizkiy; Sebastián Ventura (ISDA, 2010)

An Automatic Programming ACO-Based Algorithm for Classification Rule Mining. - Juan Luis Olmo; José María Luna; José Raúl Romero; Sebastián Ventura (PAAMS (Special Sessions and Workshops), 2010)

G3P-MI: A genetic programming algorithm for multiple instance learning. - Amelia Zafra; Sebastián Ventura (Inf. Sci., 2010)

A Survey on the Application of Genetic Programming to Classification. - Pedro G. Espejo; Sebastián Ventura; Francisco Herrera (IEEE Trans. Syst. Man Cybern. Part C, 2010)

Educational Data Mining: A Review of the State of the Art. - Cristóbal Romero 001; Sebastián Ventura (IEEE Trans. Syst. Man Cybern. Part C, 2010)

Predicting School Failure Using Data Mining. - Carlos Márquez-Vera; Cristóbal Romero 001; Sebastián Ventura (EDM, 2011)

A Java Desktop Tool for Mining Moodle Data. - Rafael Pedraza Perez; Cristóbal Romero 001; Sebastián Ventura (EDM, 2011)

JCLEC Meets WEKA! - Alberto Cano 001; José María Luna; Juan Luis Olmo; Sebastián Ventura (HAIS (1), 2011)

A Parallel Genetic Programming Algorithm for Classification. - Alberto Cano 001; Amelia Zafra; Sebastián Ventura (HAIS (1), 2011)

An EP algorithm for learning highly interpretable classifiers. - Alberto Cano 001; Amelia Zafra; Sebastián Ventura (ISDA, 2011)

Association rule mining using a multi-objective grammar-based ant programming algorithm. - Juan Luis Olmo; José María Luna; José Raúl Romero; Sebastián Ventura (ISDA, 2011)

Mining and representing rare association rules through the use of genetic programming. - José María Luna; José Raúl Romero; Sebastián Ventura (NaBIC, 2011)

RM-Tool: A framework for discovering and evaluating association rules. - Cristóbal Romero 001; José María Luna; José Raúl Romero; Sebastián Ventura (Adv. Eng. Softw., 2011)

Multiple Instance Learning with Multiple Objective Genetic Programming for Web Mining. - Amelia Zafra; Eva Lucrecia Gibaja Galindo; Sebastián Ventura (Appl. Soft Comput., 2011)

Multiple instance learning for classifying students in learning management systems. - Amelia Zafra; Cristóbal Romero 001; Sebastián Ventura (Expert Syst. Appl., 2011)

A collaborative educational association rule mining tool. - Enrique García; Cristóbal Romero 001; Sebastián Ventura; Carlos de Castro (Internet High. Educ., 2011)

A Gene Expression Programming Algorithm for Multi-Label Classification. - José Luis Ávila-Jiménez; Eva Lucrecia Gibaja Galindo; Amelia Zafra; Sebastián Ventura (J. Multiple Valued Log. Soft Comput., 2011)

Using Ant Programming Guided by Grammar for Building Rule-Based Classifiers. - Juan Luis Olmo; José Raúl Romero; Sebastián Ventura (IEEE Trans. Syst. Man Cybern. Part B, 2011)

Preface to the special issue on data mining for personalised educational systems. - Cristóbal Romero 001; Sebastián Ventura (User Model. User Adapt. Interact., 2011)

Classification via clustering for predicting final marks starting from the student participation in Forums. - Manuel Ignacio López; Cristóbal Romero 001; Sebastián Ventura; José María Luna (EDM, 2012)

Meta-learning Approach for Automatic Parameter Tuning: A case of study with educational datasets. - María De Mar Molina; Cristóbal Romero 001; Sebastián Ventura; José María Luna (EDM, 2012)

Multi-Objective Ant Programming for Mining Classification Rules. - Juan Luis Olmo; José Raúl Romero; Sebastián Ventura (EuroGP, 2012)

VisualJCLEC: A visual framework for evolutionary computation. - Juan Ignacio Jaen; José Raúl Romero; Sebastián Ventura (ISDA, 2012)

A genetic programming free-parameter algorithm for mining association rules. - José María Luna; José Raúl Romero; Cristóbal Romero 001; Sebastián Ventura (ISDA, 2012)

Binary and multiclass imbalanced classification using multi-objective ant programming. - Juan Luis Olmo; Alberto Cano 001; José Raúl Romero; Sebastián Ventura (ISDA, 2012)

Learning similarity metric to improve the performance of lazy multi-label ranking algorithms. - Oscar Gabriel Reyes Pupo; Carlos Morell 001; Sebastián Ventura (ISDA, 2012)

Multi-instance genetic programming for predicting student performance in web based educational environments. - Amelia Zafra; Sebastián Ventura (Appl. Soft Comput., 2012)

Predicción del Fracaso Escolar Mediante Técnicas de Minería de Datos. - Carlos Márquez-Vera; Cristóbal Romero 001; Sebastián Ventura Soto (Rev. Iberoam. de Tecnol. del Aprendiz., 2012)

ReliefF-MI: An extension of ReliefF to multiple instance learning. - Amelia Zafra; Mykola Pechenizkiy; Sebastián Ventura (Neurocomputing, 2012)

Design and behavior study of a grammar-guided genetic programming algorithm for mining association rules. - José María Luna; José Raúl Romero; Sebastián Ventura (Knowl. Inf. Syst., 2012)

Speeding up the evaluation phase of GP classification algorithms on GPUs. - Alberto Cano 001; Amelia Zafra; Sebastián Ventura (Soft Comput., 2012)

Classification rule mining using ant programming guided by grammar with multiple Pareto fronts. - Juan Luis Olmo; José Raúl Romero; Sebastián Ventura (Soft Comput., 2012)

Multi-objective approach based on grammar-guided genetic programming for solving multiple instance problems. - Amelia Zafra; Sebastián Ventura (Soft Comput., 2012)

ReliefF-ML: An Extension of ReliefF Algorithm to Multi-label Learning. - Oscar Gabriel Reyes Pupo; Carlos Morell 001; Sebastián Ventura Soto (CIARP (2), 2013)

A Moodle Block for Selecting, Visualizing and Mining Students' Usage Data. - Cristóbal Romero 001; Cristobal Castro; Sebastián Ventura (EDM, 2013)

A meta-learning approach for recommending a subset of white-box classification algorithms for Moodle datasets. - Cristóbal Romero 001; Juan Luis Olmo; Sebastián Ventura (EDM, 2013)

A Grammar-Guided Genetic Programming Algorithm for Multi-Label Classification. - Alberto Cano 001; Amelia Zafra; Eva Lucrecia Gibaja Galindo; Sebastián Ventura (EuroGP, 2013)

Discovering Subgroups by Means of Genetic Programming. - José María Luna; José Raúl Romero; Cristóbal Romero 001; Sebastián Ventura (EuroGP, 2013)

A novel component identification approach using evolutionary programming. - Aurora Ramírez 001; José Raúl Romero; Sebastián Ventura (GECCO (Companion), 2013)

On the use of ant programming for mining rare association rules. - Juan Luis Olmo; José Raúl Romero; Sebastián Ventura (NaBIC, 2013)

Predicting student failure at school using genetic programming and different data mining approaches with high dimensional and imbalanced data. - Carlos Márquez-Vera; Alberto Cano 001; Cristóbal Romero 001; Sebastián Ventura (Appl. Intell., 2013)

Web usage mining for predicting final marks of students that use Moodle courses. - Cristóbal Romero 001; Pedro G. Espejo; Amelia Zafra; José Raúl Romero; Sebastián Ventura (Comput. Appl. Eng. Educ., 2013)

Predicting students' final performance from participation in on-line discussion forums. - Cristóbal Romero 001; Manuel Ignacio López; José María Luna; Sebastián Ventura (Comput. Educ., 2013)

Grammar-based multi-objective algorithms for mining association rules. - José María Luna; José Raúl Romero; Sebastián Ventura (Data Knowl. Eng., 2013)

Association rule mining using genetic programming to provide feedback to instructors from multiple-choice quiz data. - Cristóbal Romero 001; Amelia Zafra; José María Luna; Sebastián Ventura (Expert Syst. J. Knowl. Eng., 2013)

Mining association rules with single and multi-objective grammar guided ant programming. - Juan Luis Olmo; José María Luna; José Raúl Romero; Sebastián Ventura (Integr. Comput. Aided Eng., 2013)

Predicting School Failure and Dropout by Using Data Mining Techniques. - Carlos Márquez-Vera; Cristóbal Romero Morales; Sebastián Ventura Soto (Rev. Iberoam. de Tecnol. del Aprendiz., 2013)

An interpretable classification rule mining algorithm. - Alberto Cano 001; Amelia Zafra; Sebastián Ventura (Inf. Sci., 2013)

HyDR-MI: A hybrid algorithm to reduce dimensionality in multiple instance learning. - Amelia Zafra; Mykola Pechenizkiy; Sebastián Ventura (Inf. Sci., 2013)

Parallel multi-objective Ant Programming for classification using GPUs. - Alberto Cano 001; Juan Luis Olmo; Sebastián Ventura (J. Parallel Distributed Comput., 2013)

DRAL: a tool for discovering relevant e-activities for learners. - Amelia Zafra; Cristóbal Romero 001; Sebastián Ventura (Knowl. Inf. Syst., 2013)

Weighted Data Gravitation Classification for Standard and Imbalanced Data. - Alberto Cano 001; Amelia Zafra; Sebastián Ventura (IEEE Trans. Cybern., 2013)

High performance evaluation of evolutionary-mined association rules on GPUs. - Alberto Cano 001; José María Luna; Sebastián Ventura (J. Supercomput., 2013)

Data mining in education. - Cristóbal Romero 001; Sebastián Ventura (WIREs Data Mining Knowl. Discov., 2013)

Accepting or Rejecting Students_ Self-grading in their Final Marks by using Data Mining. - Javier Fuentes; Cristóbal Romero 001; Carlos García-Martínez; Sebastián Ventura (EDM, 2014)

GPU-parallel subtree interpreter for genetic programming. - Alberto Cano 001; Sebastián Ventura (GECCO, 2014)

On the performance of multiple objective evolutionary algorithms for software architecture discovery. - Aurora Ramírez 001; José Raúl Romero; Sebastián Ventura (GECCO, 2014)

Classification Rule Mining with Iterated Greedy. - Juan A. Pedraza; Carlos García-Martínez; Alberto Cano 001; Sebastián Ventura (HAIS, 2014)

Reducing gaps in quantitative association rules: A genetic programming free-parameter algorithm. - José María Luna; José Raúl Romero; Cristóbal Romero 001; Sebastián Ventura (Integr. Comput. Aided Eng., 2014)

Evolutionary feature weighting to improve the performance of multi-label lazy algorithms. - Oscar Gabriel Reyes Pupo; Carlos Morell 001; Sebastián Ventura (Integr. Comput. Aided Eng., 2014)

Single and multi-objective ant programming for mining interesting rare association rules. - Juan Luis Olmo; José Raúl Romero; Sebastián Ventura (Int. J. Hybrid Intell. Syst., 2014)

Parallel evaluation of Pittsburgh rule-based classifiers on GPUs. - Alberto Cano 001; Amelia Zafra; Sebastián Ventura (Neurocomputing, 2014)

Special issue: Advances in learning schemes for function approximation. - Emilio Corchado; Ajith Abraham; Pedro Antonio Gutiérrez; José Manuel Benítez 001; Sebastián Ventura (Neurocomputing, 2014)

Foreword: Intelligent data analysis. - Sebastián Ventura; Cristóbal Romero 001; Ajith Abraham (J. Comput. Syst. Sci., 2014)

On the adaptability of G3PARM to the extraction of rare association rules. - José María Luna; José Raúl Romero; Sebastián Ventura (Knowl. Inf. Syst., 2014)

On the Use of Genetic Programming for Mining Comprehensible Rules in Subgroup Discovery. - José María Luna; José Raúl Romero; Cristóbal Romero 001; Sebastián Ventura (IEEE Trans. Cybern., 2014)

Scalable CAIM discretization on multiple GPUs using concurrent kernels. - Alberto Cano 001; Sebastián Ventura; Krzysztof J. Cios (J. Supercomput., 2014)

Multi-label learning: a review of the state of the art and ongoing research. - Eva Lucrecia Gibaja Galindo; Sebastián Ventura (WIREs Data Mining Knowl. Discov., 2014)

Swarm-based metaheuristics in automatic programming: a survey. - Juan Luis Olmo; José Raúl Romero; Sebastián Ventura (WIREs Data Mining Knowl. Discov., 2014)

Synthesis of In-Place Iterative Sorting Algorithms Using GP: A Comparison Between STGP, SFGP, G3P and GE. - David Pinheiro; Alberto Cano 001; Sebastián Ventura (EPIA, 2015)

An Extensible JCLEC-based Solution for the Implementation of Multi-Objective Evolutionary Algorithms. - Aurora Ramírez 001; José Raúl Romero; Sebastián Ventura (GECCO (Companion), 2015)

Discovering clues to avoid middle school failure at early stages. - Manuel Ángel Jiménez-Gómez; José María Luna; Cristóbal Romero 001; Sebastián Ventura (LAK, 2015)

An evolutionary algorithm for the discovery of rare class association rules in learning management systems. - José María Luna; Cristóbal Romero 001; José Raúl Romero; Sebastián Ventura (Appl. Intell., 2015)

A Tutorial on Multilabel Learning. - Eva Gibaja; Sebastián Ventura (ACM Comput. Surv., 2015)

Improving Meta-learning for Algorithm Selection by Using Multi-label Classification: A Case of Study with Educational Data Sets. - Juan Luis Olmo; Cristóbal Romero 001; Eva Gibaja; Sebastián Ventura (Int. J. Comput. Intell. Syst., 2015)

Scalable extensions of the ReliefF algorithm for weighting and selecting features on the multi-label learning context. - Oscar Gabriel Reyes Pupo; Carlos Morell 001; Sebastián Ventura (Neurocomputing, 2015)

An approach for the evolutionary discovery of software architectures. - Aurora Ramírez 001; José Raúl Romero; Sebastián Ventura (Inf. Sci., 2015)

A classification module for genetic programming algorithms in JCLEC. - Alberto Cano 001; José María Luna; Amelia Zafra; Sebastián Ventura (J. Mach. Learn. Res., 2015)

Speeding up multiple instance learning classification rules on GPUs. - Alberto Cano 001; Amelia Zafra; Sebastián Ventura (Knowl. Inf. Syst., 2015)

J. A. Larusson, B. White (eds): Learning Analytics: From Research to Practice. - Cristóbal Romero 001; Sebastián Ventura (Technol. Knowl. Learn., 2015)

Genetic Programming for Mining Association Rules in Relational Database Environments. - José María Luna; Alberto Cano 001; Sebastián Ventura (Handbook of Genetic Programming Applications, 2015)

Multiple Instance Learning - Foundations and Algorithms - Francisco Herrera; Sebastián Ventura; Rafael Bello 001; Chris Cornelis; Amelia Zafra; Dánel Sánchez Tarragó; Sarah Vluymans (Springer, 2016)

Pattern Mining with Evolutionary Algorithms - Sebastián Ventura; José María Luna (Springer, 2016)

Subgroup discovery on big data: Pruning the search space on exhaustive search algorithms. - Francisco Padillo; José María Luna; Sebastián Ventura (IEEE BigData, 2016)

A Data Structure to Speed-Up Machine Learning Algorithms on Massive Datasets. - Francisco Padillo; José María Luna; Alberto Cano 001; Sebastián Ventura (HAIS, 2016)

Mining Perfectly Rare Itemsets on Big Data: An Approach Based on Apriori-Inverse and MapReduce. - Francisco Padillo; José María Luna; Sebastián Ventura (ISDA, 2016)

Memetic Algorithms for the Automatic Discovery of Software Architectures. - Aurora Ramírez 001; Rafael Barbudo; José Raúl Romero; Sebastián Ventura (ISDA, 2016)

Subgroup Discovery on Big Data: Exhaustive Methodologies Using Map-Reduce. - Francisco Padillo; José María Luna; Sebastián Ventura (Trustcom/BigDataSE/ISPA, 2016)

Early dropout prediction using data mining: a case study with high school students. - Carlos Márquez-Vera; Alberto Cano 001; Cristóbal Romero 001; Amin Y. Noaman; Habib M. Fardoun; Sebastián Ventura (Expert Syst. J. Knowl. Eng., 2016)

A comparative study of many-objective evolutionary algorithms for the discovery of software architectures. - Aurora Ramírez 001; José Raúl Romero; Sebastián Ventura (Empir. Softw. Eng., 2016)

An Algorithm Evaluation for Discovering Classification Rules with Gene Expression Programming. - Alain Guerrero-Enamorado; Carlos Morell 001; Amin Y. Noaman; Sebastián Ventura (Int. J. Comput. Intell. Syst., 2016)

Recommending degree studies according to students' attitudes in high school by means of subgroup discovery. - Amin Y. Noaman; José María Luna; Abdul Hamid M. Ragab; Sebastián Ventura (Int. J. Comput. Intell. Syst., 2016)

LAIM discretization for multi-label data. - Alberto Cano 001; José María Luna; Eva Lucrecia Gibaja Galindo; Sebastián Ventura (Inf. Sci., 2016)

Discovering useful patterns from multiple instance data. - José María Luna; Alberto Cano 001; Virgilijus Sakalauskas; Sebastián Ventura (Inf. Sci., 2016)

Effective lazy learning algorithm based on a data gravitation model for multi-label learning. - Oscar Gabriel Reyes Pupo; Carlos Morell 001; Sebastián Ventura (Inf. Sci., 2016)

JCLAL: A Java Framework for Active Learning. - Oscar Gabriel Reyes Pupo; Eduardo Pérez; María del Carmen Rodríguez-Hernández; Habib M. Fardoun; Sebastián Ventura (J. Mach. Learn. Res., 2016)

Mining exceptional relationships with grammar-guided genetic programming. - José María Luna; Mykola Pechenizkiy; Sebastián Ventura (Knowl. Inf. Syst., 2016)

An ensemble-based approach for multi-view multi-label classification. - Eva Gibaja; Jose M. Moyano; Sebastián Ventura (Prog. Artif. Intell., 2016)

ur-CAIM: improved CAIM discretization for unbalanced and balanced data. - Alberto Cano 001; Dat T. Nguyen; Sebastián Ventura; Krzysztof J. Cios (Soft Comput., 2016)

Speeding-Up Association Rule Mining With Inverted Index Compression. - José María Luna; Alberto Cano 001; Mykola Pechenizkiy; Sebastián Ventura (IEEE Trans. Cybern., 2016)

Multi-view semi-supervised learning using genetic programming interpretable classification rules. - Carlos García-Martínez; Sebastián Ventura (CEC, 2017)

An evolutionary algorithm for optimizing the target ordering in Ensemble of Regressor Chains. - Jose M. Moyano; Eva Lucrecia Gibaja Galindo; Sebastián Ventura (CEC, 2017)

An evolutionary algorithm for mining rare association rules: A Big Data approach. - Francisco Padillo; José María Luna; Sebastián Ventura (CEC, 2017)

On the effect of local search in the multi-objective evolutionary discovery of software architectures. - Aurora Ramírez 001; José Raúl Romero; Sebastián Ventura (CEC, 2017)

Large-Scale Multi-label Ensemble Learning on Spark. - Jorge Gonzalez-Lopez; Alberto Cano 001; Sebastián Ventura (TrustCom/BigDataSE/ICESS, 2017)

Extremely high-dimensional optimization with MapReduce: Scaling functions and algorithm. - Alberto Cano 001; Carlos García-Martínez; Sebastián Ventura (Inf. Sci., 2017)

Multi-target support vector regression via correlation regressor chains. - Gabriella Melki; Alberto Cano 001; Vojislav Kecman; Sebastián Ventura (Inf. Sci., 2017)

MLDA: A tool for analyzing multi-label datasets. - Jose M. Moyano; Eva Lucrecia Gibaja Galindo; Sebastián Ventura (Knowl. Based Syst., 2017)

Exhaustive search algorithms to mine subgroups on Big Data using Apache Spark. - Francisco Padillo; José María Luna; Sebastián Ventura (Prog. Artif. Intell., 2017)

Multi-objective genetic programming for feature extraction and data visualization. - Alberto Cano 001; Sebastián Ventura; Krzysztof J. Cios (Soft Comput., 2017)

Evaluation and comparison of open source software suites for data mining and knowledge discovery. - Abdulrahman H. Altalhi; José María Luna; M. A. Vallejo; Sebastián Ventura (WIREs Data Mining Knowl. Discov., 2017)

Educational data science in massive open online courses. - Cristóbal Romero 001; Sebastián Ventura (WIREs Data Mining Knowl. Discov., 2017)

Supervised Descriptive Pattern Mining - Sebastián Ventura; José María Luna (Springer, 2018)

A gene expression programming method for multi-target regression. - Oscar Gabriel Reyes Pupo; Jose María Moyano Murillo; José María Luna; Sebastián Ventura (LOPAL, 2018)

OLLAWV: OnLine Learning Algorithm using Worst-Violators. - Gabriella Melki; Vojislav Kecman; Sebastián Ventura; Alberto Cano 001 (Appl. Soft Comput., 2018)

Distributed nearest neighbor classification for large-scale multi-label data on spark. - Jorge Gonzalez-Lopez; Sebastián Ventura; Alberto Cano 001 (Future Gener. Comput. Syst., 2018)

Mining association rules on Big Data through MapReduce genetic programming. - Francisco Padillo; José María Luna; Francisco Herrera; Sebastián Ventura (Integr. Comput. Aided Eng., 2018)

An ensemble-based method for the selection of instances in the multi-target regression problem. - Oscar Gabriel Reyes Pupo; Habib M. Fardoun; Sebastián Ventura (Integr. Comput. Aided Eng., 2018)

A gene expression programming algorithm for discovering classification rules in the multi-objective space. - Alain Guerrero-Enamorado; Carlos Morell 001; Sebastián Ventura (Int. J. Comput. Intell. Syst., 2018)

Optimization of quality measures in association rule mining: an empirical study. - José María Luna; M. Ondra; Habib M. Fardoun; Sebastián Ventura (Int. J. Comput. Intell. Syst., 2018)

A locally weighted learning method based on a data gravitation model for multi-target regression. - Oscar Gabriel Reyes Pupo; Alberto Cano 001; Habib M. Fardoun; Sebastián Ventura (Int. J. Comput. Intell. Syst., 2018)

Effective active learning strategy for multi-label learning. - Oscar Gabriel Reyes Pupo; Carlos Morell 001; Sebastián Ventura (Neurocomputing, 2018)

Review of ensembles of multi-label classifiers: Models, experimental study and prospects. - Jose M. Moyano; Eva Lucrecia Gibaja Galindo; Krzysztof J. Cios; Sebastián Ventura (Inf. Fusion, 2018)

Interactive multi-objective evolutionary optimization of software architectures. - Aurora Ramírez Quesada; José Raúl Romero; Sebastián Ventura (Inf. Sci., 2018)

Parallelization strategies for markerless human motion capture. - Alberto Cano Rojas; Enrique Yeguas-Bolivar; Rafael Muñoz-Salinas; Rafael Medina Carnicer; Sebastián Ventura (J. Real Time Image Process., 2018)

Statistical comparisons of active learning strategies over multiple datasets. - Oscar Gabriel Reyes Pupo; Abdulrahman H. Altalhi; Sebastián Ventura (Knowl. Based Syst., 2018)

MIRSVM: Multi-instance support vector machine with bag representatives. - Gabriella Melki; Alberto Cano 001; Sebastián Ventura (Pattern Recognit., 2018)

Mining Context-Aware Association Rules Using Grammar-Based Genetic Programming. - José María Luna; Mykola Pechenizkiy; María José del Jesus; Sebastián Ventura (IEEE Trans. Cybern., 2018)

Apriori Versions Based on MapReduce for Mining Frequent Patterns on Big Data. - José María Luna; Francisco Padillo; Mykola Pechenizkiy; Sebastián Ventura (IEEE Trans. Cybern., 2018)

Evolutionary Strategy to Perform Batch-Mode Active Learning on Multi-Label Data. - Oscar Gabriel Reyes Pupo; Sebastián Ventura (ACM Trans. Intell. Syst. Technol., 2018)

Obtaining Tractable and Interpretable Descriptions for Cases with Complications from a Colorectal Cancer Database. - José Antonio Delgado-Osuna; Carlos García-Martínez; Sebastián Ventura; Jose Gómez Barbadillo (CBMS, 2019)

MiNerDoc: a Semantically Enriched Text Mining System to Transform Clinical Text into Knowledge. - Carmen Luque; José María Luna; Sebastián Ventura (CBMS, 2019)

A Supervised Methodology for Analyzing Dysregulation in Splicing Machinery: An Application in Cancer Diagnosis. - Oscar Gabriel Reyes Pupo; Raúl M. Luque; Justo Castaño; Sebastián Ventura (CBMS, 2019)

Discovering Students' Engagement Behaviors in Confidence-based Assessment. - Rabia Maqsood; Paolo Ceravolo; Sebastián Ventura (EDUCON, 2019)

ARFF Data Source Library for Distributed Single/Multiple Instance, Single/Multiple Output Learning on Apache Spark. - Jorge Gonzalez-Lopez; Sebastián Ventura; Alberto Cano 001 (ICCS (3), 2019)

Associative Classification in Big Data through a G3P Approach. - José María Luna; Francisco Padillo; Sebastián Ventura (IoTBDS, 2019)

Speeding Up Classifier Chains in Multi-label Classification. - Jose M. Moyano; Eva Gibaja; Sebastián Ventura; Alberto Cano 001 (IoTBDS, 2019)

A Grammar-Guided Genetic Programing Algorithm for Associative Classification in Big Data. - Francisco Padillo; José María Luna; Sebastián Ventura (Cogn. Comput., 2019)

JCLEC-MO: A Java suite for solving many-objective optimization engineering problems. - Aurora Ramírez 001; José Raúl Romero; Carlos García-Martínez; Sebastián Ventura (Eng. Appl. Artif. Intell., 2019)

Subgroup Discovery on Multiple Instance Data. - José María Luna; Cristóbal J. Carmona; Ángel Miguel García-Vico; María José del Jesus; Sebastián Ventura (Int. J. Comput. Intell. Syst., 2019)

Virtual learning environment to predict withdrawal by leveraging deep learning. - Saeed-Ul Hassan; Hajra Waheed; Naif R. Aljohani; Mohsen Ali; Sebastián Ventura; Francisco Herrera (Int. J. Intell. Syst., 2019)

Performing Multi-Target Regression via a Parameter Sharing-Based Deep Network. - Oscar Gabriel Reyes Pupo; Sebastián Ventura (Int. J. Neural Syst., 2019)

An evolutionary approach to build ensembles of multi-label classifiers. - Jose M. Moyano; Eva Lucrecia Gibaja Galindo; Krzysztof J. Cios; Sebastián Ventura (Inf. Fusion, 2019)

A survey of many-objective optimisation in search-based software engineering. - Aurora Ramírez 001; José Raúl Romero; Sebastián Ventura (J. Syst. Softw., 2019)

LEAC: An efficient library for clustering with evolutionary algorithms. - Hermes Robles-Berumen; Amelia Zafra; Habib M. Fardoun; Sebastián Ventura (Knowl. Based Syst., 2019)

WordificationMI: multi-relational data mining through multiple-instance propositionalization. - Luis A. Quintero-Domínguez; Carlos Morell 001; Sebastián Ventura (Prog. Artif. Intell., 2019)

Guest Editorial: Special Issue on Early Prediction and Supporting of Learning Performance. - Cristóbal Romero 001; Sebastián Ventura (IEEE Trans. Learn. Technol., 2019)

Frequent itemset mining: A 25 years review. - José María Luna; Philippe Fournier-Viger; Sebastián Ventura (WIREs Data Mining Knowl. Discov., 2019)

An advanced review on text mining in medicine. - Carmen Luque; José María Luna; Maria Luque; Sebastián Ventura (WIREs Data Mining Knowl. Discov., 2019)

A Preliminary Study on Evolutionary Clustering for Multiple Instance Learning. - Aurora Esteban; Amelia Zafra; Sebastián Ventura (CEC, 2020)

Tree-Shaped Ensemble of Multi-Label Classifiers using Grammar-Guided Genetic Programming. - Jose M. Moyano; Eva Lucrecia Gibaja Galindo; Krzysztof J. Cios; Sebastián Ventura (CEC, 2020)

Generating Ensembles of Multi-Label Classifiers Using Cooperative Coevolutionary Algorithms. - Jose M. Moyano; Eva L. Gibaja; Krzysztof J. Cios; Sebastián Ventura (ECAI, 2020)

Mining Cross-Level High Utility Itemsets. - Philippe Fournier-Viger; Ying Wang; Jerry Chun-Wei Lin; José María Luna; Sebastián Ventura (IEA/AIE, 2020)

Fast Convergence of Competitive Spiking Neural Networks with Sample-Based Weight Initialization. - Paolo Gabriel Cachi; Sebastián Ventura; Krzysztof Jozef Cios (IPMU (3), 2020)

Extracting User-Centric Knowledge on Two Different Spaces: Concepts and Records. - José María Luna; Philippe Fournier-Viger; Sebastián Ventura (IEEE Access, 2020)

Exceptional in so Many Ways - Discovering Descriptors That Display Exceptional Behavior on Contrasting Scenarios. - José María Luna; Mykola Pechenizkiy; Wouter Duivesteijn; Sebastián Ventura (IEEE Access, 2020)

A supervised machine learning-based methodology for analyzing dysregulation in splicing machinery: An application in cancer diagnosis. - Oscar Gabriel Reyes Pupo; Eduardo Pérez; Raúl M. Luque; Justo Castaño; Sebastián Ventura (Artif. Intell. Medicine, 2020)

Multi-view Genetic Programming Learning to Obtain Interpretable Rule-Based Classifiers for Semi-supervised Contexts. Lessons Learnt. - Carlos García-Martínez; Sebastián Ventura (Int. J. Comput. Intell. Syst., 2020)

Heuristics for interesting class association rule mining a colorectal cancer database. - José A. Delgado-Osuna; Carlos García-Martínez; Jose Gómez Barbadillo; Sebastián Ventura (Inf. Process. Manag., 2020)

Distributed multi-label feature selection using individual mutual information measures. - Jorge Gonzalez-Lopez; Sebastián Ventura; Alberto Cano 001 (Knowl. Based Syst., 2020)

Predicting literature's early impact with sentiment analysis in Twitter. - Saeed-Ul Hassan; Naif R. Aljohani; Nimra Idrees; Raheem Sarwar; Raheel Nawaz; Eugenio Martínez-Cámara; Sebastián Ventura; Francisco Herrera (Knowl. Based Syst., 2020)

Combining multi-label classifiers based on projections of the output space using Evolutionary algorithms. - Jose M. Moyano; Eva Gibaja; Krzysztof J. Cios; Sebastián Ventura (Knowl. Based Syst., 2020)

LAC: Library for associative classification. - Francisco Padillo; José María Luna; Sebastián Ventura (Knowl. Based Syst., 2020)

Tweet Coupling: a social media methodology for clustering scientific publications. - Saeed-Ul Hassan; Naif R. Aljohani; Mudassir Shabbir; Umair Ali; Sehrish Iqbal; Raheem Sarwar; Eugenio Martínez-Cámara; Sebastián Ventura; Francisco Herrera (Scientometrics, 2020)

Distributed Selection of Continuous Features in Multilabel Classification Using Mutual Information. - Jorge Gonzalez-Lopez; Sebastián Ventura; Alberto Cano 001 (IEEE Trans. Neural Networks Learn. Syst., 2020)

Educational data mining and learning analytics: An updated survey. - Cristóbal Romero 001; Sebastián Ventura (WIREs Data Mining Knowl. Discov., 2020)

A semantically enriched text mining system for clinical decision support. - Carmen Luque; José Miguel Madueño Luna; Sebastián Ventura (Comput. Intell., 2021)

EDITORIAL. - Sebastián Ventura; Paolo Soda; Alejandro Rodríguez González (Comput. Intell., 2021)

A propositionalization method of multi-relational data based on Grammar-Guided Genetic Programming. - Luis A. Quintero-Domínguez; Carlos Morell 001; Sebastián Ventura (Expert Syst. Appl., 2021)

CRBA: A Competitive Rate-Based Algorithm Based on Competitive Spiking Neural Networks. - Paolo Gabriel Cachi; Sebastián Ventura; Krzysztof J. Cios (Frontiers Comput. Neurosci., 2021)

Performing multi-target regression via gene expression programming-based ensemble models. - Jose M. Moyano; Oscar Gabriel Reyes Pupo; Habib M. Fardoun; Sebastián Ventura (Neurocomputing, 2021)

Introduction to the special issue on Methods and applications in the analysis of social data in healthcare. - Alejandro Rodríguez González; Sebastián Ventura Soto; Paolo Soda; Jesualdo Tomás Fernández-Breis (Inf. Process. Manag., 2021)

Mining local periodic patterns in a discrete sequence. - Philippe Fournier-Viger; Peng Yang; Rage Uday Kiran; Sebastián Ventura; José María Luna (Inf. Sci., 2021)

Peer assessment using soft computing techniques. - Maricela Pinargote-Ortega; Lorena Bowen-Mendoza; Jaime Meza; Sebastián Ventura (J. Comput. High. Educ., 2021)

Convolutional neural networks for the automatic diagnosis of melanoma: An extensive experimental study. - Eduardo Pérez; Oscar Gabriel Reyes Pupo; Sebastián Ventura (Medical Image Anal., 2021)

An Efficient 2-Stages Classification Model for Students Performance Prediction. - Mohamed Farouk Yacoub; Huda Amin Maghawry; Nivin A. Helal; Sebastián Ventura Soto; Tarek F. Gharib (AISI, 2022)

Smart Operators for Inducing Colorectal Cancer Classification Trees with PonyGE2 Grammatical Evolution Python Package. - José A. Delgado-Osuna; Carlos García-Martínez; Sebastián Ventura (CEC, 2022)

Dynamic Airline Discounts using an Evolutionary Subgroup Discovery Methodology. - Marco Antonio Barron; José María Luna; Sebastián Ventura (COINS, 2022)

Improving the Performance of Multi-Label Classifiers via Label Space Reduction. - Jose M. Moyano; José María Luna; Sebastián Ventura (COINS, 2022)

Multi-view Deep Neural Networks for multiclass skin lesion diagnosis. - Eduardo Pérez; Sebastián Ventura (COINS, 2022)

Reproducing Aplysia R-15 Bursting Neurodynamics on a Neuromorphic Microchip. - Paolo Gabriel Cachi; Soumil Jain; Sebastián Ventura; Gert Cauwenberghs; Krzysztof J. Cios (ICECS 2022, 2022)

Facing Up Fare War: Generating Competitive Price Models With Gene Expression Programming. - Marco Antonio Barron; José María Luna; Sebastián Ventura (IEEE Access, 2022)

Reducing the Label Space a Predefined Ratio for a More Efficient Multilabel Classification. - Jose M. Moyano; José María Luna; Sebastián Ventura (IEEE Access, 2022)

Course Recommendation based on Sequences: An Evolutionary Search of Emerging Sequential Patterns. - Mohammed Ibrahim Al-Twijri; José María Luna; Francisco Herrera; Sebastián Ventura (Cogn. Comput., 2022)

MT-SNN: Spiking Neural Network that Enables Single-Tasking of Multiple Tasks. - Paolo Gabriel Cachi; Sebastián Ventura; Krzysztof J. Cios (CoRR, 2022)

Improving the understanding of cancer in a descriptive way: An emerging pattern mining-based approach. - Antonio Manuel Trasierras; José María Luna; Sebastián Ventura (Int. J. Intell. Syst., 2022)

Subgroup discovery in MOOCs: a big data application for describing different types of learners. - José María Luna; Habib M. Fardoun; Francisco Padillo; Cristóbal Romero 001; Sebastián Ventura (Interact. Learn. Environ., 2022)

Auto-adaptive Grammar-Guided Genetic Programming algorithm to build Ensembles of Multi-Label Classifiers. - Jose M. Moyano; Sebastián Ventura (Inf. Fusion, 2022)

Design of peer assessment rubrics for ICT topics. - Lorena Bowen-Mendoza; Maricela Pinargote-Ortega; Jaime Meza; Sebastián Ventura (J. Comput. High. Educ., 2022)

Modeling and predicting students' engagement behaviors using mixture Markov models. - Rabia Maqsood; Paolo Ceravolo; Cristóbal Romero 001; Sebastián Ventura (Knowl. Inf. Syst., 2022)

An ensemble-based convolutional neural network model powered by a genetic algorithm for melanoma diagnosis. - Eduardo Pérez; Sebastián Ventura (Neural Comput. Appl., 2022)

Data mining in predictive maintenance systems: A taxonomy and systematic review. - Aurora Esteban; Amelia Zafra; Sebastián Ventura (WIREs Data Mining Knowl. Discov., 2022)

A Comparison of Neural Network-Based Super-Resolution Models on 3D Rendered Images. - Rafael Berral-Soler; Francisco José Madrid-Cuevas; Sebastián Ventura; Rafael Muñoz-Salinas; Manuel J. Marín-Jiménez (CAIP (1), 2023)

Radiomics Software Tools: A comparative Analysis on Breast Cancer. - Eduardo Almeda Luna; José María Luna; Sebastián Ventura (CBMS, 2023)

A Novel Genetic Algorithm with Specialized Genetic Operators for Clustering. - Hermes Robles-Berumen; Amelia Zafra; Sebastián Ventura (HAIS, 2023)

TM-SNN: Threshold Modulated Spiking Neural Network for Multi-task Learning. - Paolo Gabriel Cachi; Sebastián Ventura Soto; Krzysztof J. Cios (IWANN (2), 2023)

Selecting the Best Approach for Predicting Student Dropout in Full Online Private Higher Education. - Jose Manuel Porras; Antonio Porras; José Alberto Fernández; Cristóbal Romero 001; Sebastián Ventura (LASI Spain, 2023)

A Case-Study Comparison of Machine Learning Approaches for Predicting Student's Dropout from Multiple Online Educational Entities. - Jose Manuel Porras; Juan Alfonso Lara; Cristóbal Romero 001; Sebastián Ventura (Algorithms, 2023)

Progressive growing of Generative Adversarial Networks for improving data augmentation and skin cancer diagnosis. - Eduardo Pérez; Sebastián Ventura (Artif. Intell. Medicine, 2023)

A framework to build accurate Convolutional Neural Network models for melanoma diagnosis. - Eduardo Pérez; Sebastián Ventura (Knowl. Based Syst., 2023)

Efficient mining of top-k high utility itemsets through genetic algorithms. - José María Luna; Rage Uday Kiran; Philippe Fournier-Viger; Sebastián Ventura (Inf. Sci., 2023)

Improving Spiking Neural Network Performance with Auxiliary Learning. - Paolo Gabriel Cachi; Sebastián Ventura; Krzysztof J. Cios (Mach. Learn. Knowl. Extr., 2023)

A contrast set mining based approach for cancer subtype analysis. - Antonio Manuel Trasierras; José María Luna; Sebastián Ventura (Artif. Intell. Medicine, 2023)

Eight years of AutoML: categorisation, review and trends. - Rafael Barbudo; Sebastián Ventura; José Raúl Romero (Knowl. Inf. Syst., 2023)

Comprehensive Study on Sentiment Analysis: Insights Into Data Preprocessing, Feature Extraction, and Deep Learning Model Selection. - Ibtissam Youb; Sebastián Ventura (SADASC (1), 2024)

Efficient Frequent Chronicle Mining Algorithms: Application to Sleep Disorder. - Hareth Zmezm; José María Luna; Eduardo Almeda Luna; Sebastián Ventura (IEEE Access, 2024)

Introduction to the special issue on recent advances on digital economy-oriented artificial intelligence. - Yu-Lin He; Philippe Fournier-Viger; Sebastián Ventura; Ling Zhang (Eng. Appl. Artif. Intell., 2024)

StaTDS library: Statistical tests for Data Science. - Christian Luna; Antonio R. Moya; José María Luna; Sebastián Ventura (Neurocomputing, 2024)

Data heterogeneity's impact on the performance of frequent itemset mining algorithms. - Antonio Manuel Trasierras; José María Luna; Philippe Fournier-Viger; Sebastián Ventura (Inf. Sci., 2024)

Hoeffding adaptive trees for multi-label classification on data streams. - Aurora Esteban; Alberto Cano 001; Amelia Zafra; Sebastián Ventura (Knowl. Based Syst., 2024)

A survey of genetic algorithms for clustering: Taxonomy and empirical analysis. - Hermes Robles-Berumen; Amelia Zafra; Sebastián Ventura (Swarm Evol. Comput., 2024)

A deep learning model for Alzheimer's disease diagnosis based on patient clinical records. - José Luis Ávila-Jiménez; Vanesa Cantón-Habas; María del Pilar Carrera-González; Manuel Rich-Ruiz; Sebastián Ventura (Comput. Biol. Medicine, 2024)

Improving hyper-parameter self-tuning for data streams by adapting an evolutionary approach. - Antonio R. Moya; Bruno Veloso; João Gama 001; Sebastián Ventura (Data Min. Knowl. Discov., 2024)

Handling imbalanced medical datasets: review of a decade of research. - Mabrouka Salmi; Dalia Atif; Diego Oliva; Ajith Abraham; Sebastián Ventura (Artif. Intell. Rev., 2024)

Deep Learning Approaches to Assessing University Students' Health-Related Quality of Life: A Comparative Study of MLP and GNN. - José Luis Ávila-Jiménez; Manuel Rich-Ruiz; Francisco J. Rodríguez-Lozano; Vanesa Cantón-Habas; Sebastián Ventura (CBMS, 2025)

Fuzzy Logic Recommender Model for Housing. - Emanuel G. Muñoz; Jaime Meza; Sebastián Ventura (IEEE Access, 2025)

Mining autonomous student patterns score on LMS within online higher education. - Ricardo Ordoñez-Avila; Jaime Meza; Sebastián Ventura (PeerJ Comput. Sci., 2025)

Weak Supervision: A Survey on Predictive Maintenance. - Antonio-Manuel Martínez-Heredia; Sebastián Ventura (WIREs Data. Mining. Knowl. Discov., 2025)