The Role of Interval Initialization in a GBML System with Rule Representation and Adaptive Discrete Intervals. - Jaume Bacardit; Josep Maria Garrell i Guiu (CCIA, 2002)

Evolution Of Adaptive Discretization Intervals For A Rule-based Genetic Learning System. - Jaume Bacardit; Josep Maria Garrell i Guiu (GECCO, 2002)

Evolution of Multi-adaptive Discretization Intervals for a Rule-Based Genetic Learning System. - Jaume Bacardit; Josep Maria Garrell i Guiu (IBERAMIA, 2002)

Evolving Multiple Discretizations with Adaptive Intervals for a Pittsburgh Rule-Based Learning Classifier System. - Jaume Bacardit; Josep Maria Garrell i Guiu (GECCO, 2003)

Experimental Evaluation of Discretization Schemes for Rule Induction. - Jesús S. Aguilar-Ruiz; Jaume Bacardit; Federico Divina (GECCO (1), 2004)

Analysis and Improvements of the Adaptive Discretization Intervals Knowledge Representation. - Jaume Bacardit; Josep Maria Garrell i Guiu (GECCO (2), 2004)

Speeding-Up Pittsburgh Learning Classifier Systems: Modeling Time and Accuracy. - Jaume Bacardit; David E. Goldberg; Martin V. Butz; Xavier Llorà; Josep Maria Garrell i Guiu (PPSN, 2004)

Analysis of the initialization stage of a Pittsburgh approach learning classifier system. - Jaume Bacardit (GECCO, 2005)

Data Mining in Learning Classifier Systems: Comparing XCS with GAssist. - Jaume Bacardit; Martin V. Butz (IWLCS, 2005)

Bloat Control and Generalization Pressure Using the Minimum Description Length Principle for a Pittsburgh Approach Learning Classifier System. - Jaume Bacardit; Josep Maria Garrell i Guiu (IWLCS, 2005)

Improving the Performance of a Pittsburgh Learning Classifier System Using a Default Rule. - Jaume Bacardit; David E. Goldberg; Martin V. Butz (IWLCS, 2005)

From HP Lattice Models to Real Proteins: Coordination Number Prediction Using Learning Classifier Systems. - Michael Stout; Jaume Bacardit; Jonathan D. Hirst; Natalio Krasnogor; Jacek Blazewicz (EvoWorkshops, 2006)

Smart crossover operator with multiple parents for a Pittsburgh learning classifier system. - Jaume Bacardit; Natalio Krasnogor (GECCO, 2006)

Coordination number prediction using learning classifier systems: performance and interpretability. - Jaume Bacardit; Michael Stout; Natalio Krasnogor; Jonathan D. Hirst; Jacek Blazewicz (GECCO, 2006)

Automated alphabet reduction method with evolutionary algorithms for protein structure prediction. - Jaume Bacardit; Michael Stout; Jonathan D. Hirst; Kumara Sastry; Xavier Llorà; Natalio Krasnogor (GECCO, 2007)

Learning Classifier Systems: Looking Back and Glimpsing Ahead. - Jaume Bacardit; Ester Bernadó-Mansilla; Martin V. Butz (IWLCS, 2007)

Empirical Evaluation of Ensemble Techniques for a Pittsburgh Learning Classifier System. - Jaume Bacardit; Natalio Krasnogor (IWLCS, 2007)

Fast rule representation for continuous attributes in genetics-based machine learning. - Jaume Bacardit; Natalio Krasnogor (GECCO, 2008)

Learning classifier systems for optimisation problems: a case study on fractal travelling salesman problem. - Maximiliano Tabacman; Natalio Krasnogor; Jaume Bacardit; Irene Loiseau (GECCO (Companion), 2008)

Prediction of recursive convex hull class assignments for protein residues. - Michael Stout; Jaume Bacardit; Jonathan D. Hirst; Natalio Krasnogor (Bioinform., 2008)

Data Mining in Proteomics with Learning Classifier Systems. - Jaume Bacardit; Michael Stout; Jonathan D. Hirst; Natalio Krasnogor (Learning Classifier Systems in Data Mining, 2008)

A mixed discrete-continuous attribute list representation for large scale classification domains. - Jaume Bacardit; Natalio Krasnogor (GECCO, 2009)

Automated Alphabet Reduction for Protein Datasets. - Jaume Bacardit; Michael Stout; Jonathan D. Hirst; Alfonso Valencia; Robert Elliott Smith; Natalio Krasnogor (BMC Bioinform., 2009)

Performance and Efficiency of Memetic Pittsburgh Learning Classifier Systems. - Jaume Bacardit; Natalio Krasnogor (Evol. Comput., 2009)

Improving the scalability of rule-based evolutionary learning. - Jaume Bacardit; Edmund K. Burke; Natalio Krasnogor (Memetic Comput., 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)

Prediction of topological contacts in proteins using learning classifier systems. - Michael Stout; Jaume Bacardit; Jonathan D. Hirst; Robert Elliott Smith; Natalio Krasnogor (Soft Comput., 2009)

Speeding up the evaluation of evolutionary learning systems using GPGPUs. - María A. Franco; Natalio Krasnogor; Jaume Bacardit (GECCO, 2010)

Evolutionary symbolic discovery for bioinformatics, systems and synthetic biology. - Pawel Widera; Jaume Bacardit; Natalio Krasnogor; Carlos García-Martínez; Manuel Lozano 001 (GECCO (Companion), 2010)

A learning classifier system with mutual-information-based fitness. - Robert Elliott Smith; Max Kun Jiang; Jaume Bacardit; Michael Stout; Natalio Krasnogor; Jonathan D. Hirst (Evol. Intell., 2010)

Guest Editorial: Thematic Issue on 'Metaheuristics for large scale data mining'. - Jaume Bacardit; Xavier Llorà (Memetic Comput., 2010)

Modelling the initialisation stage of the ALKR representation for discrete domains and GABIL encoding. - María A. Franco; Natalio Krasnogor; Jaume Bacardit (GECCO, 2011)

A NSGA-II Algorithm for the Residue-Residue Contact Prediction. - Alfonso E. Márquez Chamorro; Federico Divina; Jesús S. Aguilar-Ruiz; Jaume Bacardit; Gualberto Asencio-Cortés; Cosme Ernesto Santiesteban-Toca (EvoBIO, 2012)

Post-processing operators for decision lists. - María A. Franco; Natalio Krasnogor; Jaume Bacardit (GECCO, 2012)

Contact map prediction using a large-scale ensemble of rule sets and the fusion of multiple predicted structural features. - Jaume Bacardit; Pawel Widera; Alfonso E. Márquez Chamorro; Federico Divina; Jesús S. Aguilar-Ruiz; Natalio Krasnogor (Bioinform., 2012)

Analysing BioHEL using challenging boolean functions. - María A. Franco; Natalio Krasnogor; Jaume Bacardit (Evol. Intell., 2012)

An efficient decision rule-based system for the protein residue-residue contact prediction. - Alfonso E. Márquez Chamorro; Federico Divina; Jaume Bacardit; Jesús S. Aguilar-Ruiz (IEEE Congress on Evolutionary Computation, 2013)

Integrating memetic search into the BioHEL evolutionary learning system for large-scale datasets. - Dan Andrei Calian; Jaume Bacardit (Memetic Comput., 2013)

GAssist vs. BioHEL: critical assessment of two paradigms of genetics-based machine learning. - María A. Franco; Natalio Krasnogor; Jaume Bacardit (Soft Comput., 2013)

Large-scale data mining using genetics-based machine learning. - Jaume Bacardit; Xavier Llorà (WIREs Data Mining Knowl. Discov., 2013)

A combined MapReduce-windowing two-level parallel scheme for evolutionary prototype generation. - Isaac Triguero; Daniel Peralta; Jaume Bacardit; Salvador García 001; Francisco Herrera (IEEE Congress on Evolutionary Computation, 2014)

Hard Data Analytics Problems Make for Better Data Analysis Algorithms: Bioinformatics as an Example. - Jaume Bacardit; Pawel Widera; Nicola Lazzarini; Natalio Krasnogor (Big Data, 2014)

Large-Scale Experimental Evaluation of Cluster Representations for Multiobjective Evolutionary Clustering. - Alvaro Garcia-Piquer; Albert Fornells; Jaume Bacardit; Albert Orriols-Puig; Elisabet Golobardes (IEEE Trans. Evol. Comput., 2014)

Enhancing the scalability of a genetic algorithm to discover quantitative association rules in large-scale datasets. - María Martínez-Ballesteros; Jaume Bacardit; Alicia Troncoso Lora; José C. Riquelme (Integr. Comput. Aided Eng., 2015)

MRPR: A MapReduce solution for prototype reduction in big data classification. - Isaac Triguero; Daniel Peralta; Jaume Bacardit; Salvador García 001; Francisco Herrera (Neurocomputing, 2015)

ROSEFW-RF: The winner algorithm for the ECBDL'14 big data competition: An extremely imbalanced big data bioinformatics problem. - Isaac Triguero; Sara del Río; Victoria López; Jaume Bacardit; José Manuel Benítez 001; Francisco Herrera (Knowl. Based Syst., 2015)

Functional networks inference from rule-based machine learning models. - Nicola Lazzarini; Pawel Widera; Stuart Williamson; Rakesh Heer; Natalio Krasnogor; Jaume Bacardit (BioData Min., 2016)

Large-scale experimental evaluation of GPU strategies for evolutionary machine learning. - María A. Franco; Jaume Bacardit (Inf. Sci., 2016)

GPU-SME-kNN: Scalable and memory efficient kNN and lazy learning using GPUs. - Pablo David Gutiérrez; Miguel Lastra; Jaume Bacardit; José Manuel Benítez 001; Francisco Herrera (Inf. Sci., 2016)

Characterising the Influence of Rule-Based Knowledge Representations in Biological Knowledge Extraction from Transcriptomics Data. - Simon Baron; Nicola Lazzarini; Jaume Bacardit (EvoApplications (1), 2017)

RGIFE: a ranked guided iterative feature elimination heuristic for the identification of biomarkers. - Nicola Lazzarini; Jaume Bacardit (BMC Bioinform., 2017)

Scaling-up multiobjective evolutionary clustering algorithms using stratification. - Alvaro Garcia-Piquer; Jaume Bacardit; Albert Fornells; Elisabet Golobardes (Pattern Recognit. Lett., 2017)

A Combined Deep Learning GRU-Autoencoder for the Early Detection of Respiratory Disease in Pigs Using Multiple Environmental Sensors. - Jake Cowton; Ilias Kyriazakis; Thomas Plötz; Jaume Bacardit (Sensors, 2018)

Artificial Life in a Challenged World. - Harold Fellermann; Jaume Bacardit; Ángel Goñi-Moreno; Rudolf M. Füchslin (ALIFE, 2019)

Towards Low-Carbon Conferencing: Acceptance of Virtual Conferencing Solutions and Other Sustainability Measures in the ALIFE Community. - Harold Fellermann; Alexandra S. Penn; Rudolf M. Füchslin; Jaume Bacardit; Ángel Goñi-Moreno (ALIFE, 2019)

Automated Individual Pig Localisation, Tracking and Behaviour Metric Extraction Using Deep Learning. - Jake Cowton; Ilias Kyriazakis; Jaume Bacardit (IEEE Access, 2019)

Multi-classifier prediction of knee osteoarthritis progression from incomplete imbalanced longitudinal data. - Pawel Widera; Paco M. J. Welsing; Christoph Ladel; John Loughlin; Floris P. F. J. Lafeber; Florence Petit Dop; Jonathan Larkin; Harrie Weinans; Ali Mobasheri; Jaume Bacardit (CoRR, 2019)

Decoding human fetal liver haematopoiesis. - Dorin-Mirel Popescu; Rachel A. Botting; Emily Stephenson; Kile Green; Simone Webb; Laura Jardine; Emily F. Calderbank; Krzysztof Polanski; Issac Goh; Mirjana Efremova; Meghan Acres; Daniel Maunder; et al. (Nat., 2019)

Insight from data analytics with an automotive aftermarket SME. - Wayne S. Smith; Shirley Coleman; Jaume Bacardit; Syd Coxon (Qual. Reliab. Eng. Int., 2019)

Automatic Tuning of Rule-Based Evolutionary Machine Learning via Problem Structure Identification. - María A. Franco; Natalio Krasnogor; Jaume Bacardit (IEEE Comput. Intell. Mag., 2020)

Detection of FLOSS version release events from Stack Overflow message data. - Artur Sokolovsky; Thomas Gross 001; Jaume Bacardit (CoRR, 2020)

Interpretable ML-driven Strategy for Automated Trading Pattern Extraction. - Artur Sokolovsky; Luca Arnaboldi 001; Jaume Bacardit; Thomas Gross 001 (CoRR, 2021)

Computational Strategies for the Identification of a Transcriptional Biomarker Panel to Sense Cellular Growth States in Bacillus subtilis. - Yiming Huang; Wendy Smith; Colin Harwood; Anil Wipat; Jaume Bacardit (Sensors, 2021)

McCall, David Walker: The intersection of evolutionary computation and explainable AI. - Jaume Bacardit; Alexander E. I. Brownlee; Stefano Cagnoni; Giovanni Iacca; John A. W (GECCO Companion, 2022)

Benchmark time series data sets for PyTorch - the torchtime package. - Philip Darke; Paolo Missier; Jaume Bacardit (CoRR, 2022)

Curating a longitudinal research resource using linked primary care EHR data - a UK Biobank case study. - Philip Darke; Sophie A. Cassidy; Michael Catt; Roy Taylor; Paolo Missier; Jaume Bacardit (J. Am. Medical Informatics Assoc., 2022)

Insight from data analytics in a facilities management company. - Daniel Walker; Martin Ruane; Jaume Bacardit; Shirley Coleman (Qual. Reliab. Eng. Int., 2022)

Estimating individual-level pig growth trajectories from group-level weight time series using machine learning. - Christian Taylor; Jonathan Guy; Jaume Bacardit (Comput. Electron. Agric., 2023)

Deep learning identification of coronary artery disease from bilateral finger photoplethysmography sensing: A proof-of-concept study. - Sadaf Iqbal; Sharad Agarwal; Ian Purcell; Alan Murray; Jaume Bacardit; John Allen (Biomed. Signal Process. Control., 2023)

Evolutionary Computation and Explainable AI: A Roadmap to Transparent Intelligent Systems. - Ryan Zhou; Jaume Bacardit; Alexander E. I. Brownlee; Stefano Cagnoni; Martin Fyvie; Giovanni Iacca; John A. W. McCall; Niki van Stein; David Walker 003; Ting Hu 001 (CoRR, 2024)

Introduction to the Special Issue on Explainable AI in Evolutionary Computation. - Jaume Bacardit; Alexander E. I. Brownlee; Stefano Cagnoni; Giovanni Iacca; John A. W. McCall; David J. Walker (ACM Trans. Evol. Learn. Optim., 2024)

Introduction to the Special Issue on Explainable AI in Evolutionary Computation - Part 2. - Jaume Bacardit; Alexander E. I. Brownlee; Stefano Cagnoni; Giovanni Iacca; John McCall 001; David Walker 003 (ACM Trans. Evol. Learn. Optim., 2025)