Jaume Bacardit

Publication Activity (10 Years)

Years Active: 2002-2024
Publications (10 Years): 25

Top Topics

Machine Learning

Top Venues

Qual. Reliab. Eng. Int.

Publications

Jaume Bacardit, Alexander E. I. Brownlee, Stefano Cagnoni, Giovanni Iacca, John A. W. McCall, David J. Walker
Introduction to the Special Issue on Explainable AI in Evolutionary Computation. ACM Trans. Evol. Learn. Optim. 4 (1) (2024)
Ryan Zhou, Jaume Bacardit, Alexander E. I. Brownlee, Stefano Cagnoni, Martin Fyvie, Giovanni Iacca, John A. W. McCall, Niki van Stein, David Walker, Ting Hu
Evolutionary Computation and Explainable AI: A Roadmap to Transparent Intelligent Systems. CoRR (2024)
Sadaf Iqbal, Sharad Agarwal, Ian Purcell, Alan Murray, Jaume Bacardit, John Allen
Deep learning identification of coronary artery disease from bilateral finger photoplethysmography sensing: A proof-of-concept study. Biomed. Signal Process. Control. 86 (Part A) (2023)
Christian Taylor, Jonathan Guy, Jaume Bacardit
Estimating individual-level pig growth trajectories from group-level weight time series using machine learning. Comput. Electron. Agric. 208 (2023)
Philip Darke, Sophie Cassidy, Michael Catt, Roy Taylor, Paolo Missier, Jaume Bacardit
Curating a longitudinal research resource using linked primary care EHR data - a UK Biobank case study. J. Am. Medical Informatics Assoc. 29 (3) (2022)
Daniel Walker, Martin Ruane, Jaume Bacardit, Shirley Coleman
Insight from data analytics in a facilities management company. Qual. Reliab. Eng. Int. 38 (3) (2022)
Jaume Bacardit, Alexander E. I. Brownlee, Stefano Cagnoni, Giovanni Iacca, John A. W
McCall, David Walker: The intersection of evolutionary computation and explainable AI. GECCO Companion (2022)
Philip Darke, Paolo Missier, Jaume Bacardit
Benchmark time series data sets for PyTorch - the torchtime package. CoRR (2022)
Artur Sokolovsky, Luca Arnaboldi, Jaume Bacardit, Thomas Gross
Interpretable ML-driven Strategy for Automated Trading Pattern Extraction. CoRR (2021)
Yiming Huang, Wendy Smith, Colin Harwood, Anil Wipat, Jaume Bacardit
Computational Strategies for the Identification of a Transcriptional Biomarker Panel to Sense Cellular Growth States in Bacillus subtilis. Sensors 21 (7) (2021)
María A. Franco, Natalio Krasnogor, Jaume Bacardit
Automatic Tuning of Rule-Based Evolutionary Machine Learning via Problem Structure Identification. IEEE Comput. Intell. Mag. 15 (3) (2020)
Artur Sokolovsky, Thomas Gross, Jaume Bacardit
Detection of FLOSS version release events from Stack Overflow message data. CoRR (2020)
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, Peter Vegh, Yorick Gitton, Jong-Eun Park, Roser Vento-Tormo, Zhichao Miao, David Dixon, Rachel Rowell, David McDonald, James Fletcher, Elizabeth Poyner, Gary Reynolds, Michael Mather, Corina Moldovan, Lira Mamanova, Frankie Greig, Matthew D. Young, Kerstin B. Meyer, Steven Lisgo, Jaume Bacardit, Andrew Fuller, Ben Millar, Barbara Innes, Susan Lindsay, Michael J. T. Stubbington, Monika S. Kowalczyk, Bo Li, Orr Ashenberg, Marcin Tabaka, Danielle Dionne, Timothy L. Tickle, Michal Slyper, Orit Rozenblatt-Rosen, Andrew Filby, Peter Carey, Alexandra-Chloé Villani, Anindita Roy, Aviv Regev, Alain Chédotal, Irene Roberts, Berthold Göttgens, Sam Behjati, Elisa Laurenti, Sarah A. Teichmann, Muzlifah Haniffa
Decoding human fetal liver haematopoiesis. Nat. 574 (7778) (2019)
Harold Fellermann, Alexandra S. Penn, Rudolf M. Füchslin, Jaume Bacardit, Ángel Goñi Moreno
Towards Low-Carbon Conferencing: Acceptance of Virtual Conferencing Solutions and Other Sustainability Measures in the ALIFE Community. ALIFE (2019)
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
Multi-classifier prediction of knee osteoarthritis progression from incomplete imbalanced longitudinal data. CoRR (2019)
Wayne S. Smith, Shirley Coleman, Jaume Bacardit, Syd Coxon
Insight from data analytics with an automotive aftermarket SME. Qual. Reliab. Eng. Int. 35 (5) (2019)
Jake Cowton, Ilias Kyriazakis, Jaume Bacardit
Automated Individual Pig Localisation, Tracking and Behaviour Metric Extraction Using Deep Learning. IEEE Access 7 (2019)
Harold Fellermann, Jaume Bacardit, Ángel Goñi Moreno, Rudolf M. Füchslin
Artificial Life in a Challenged World. ALIFE (2019)
Jake Cowton, Ilias Kyriazakis, Thomas Plötz, Jaume Bacardit
A Combined Deep Learning GRU-Autoencoder for the Early Detection of Respiratory Disease in Pigs Using Multiple Environmental Sensors. Sensors 18 (8) (2018)
Alvaro Garcia-Piquer, Jaume Bacardit, Albert Fornells, Elisabet Golobardes
Scaling-up multiobjective evolutionary clustering algorithms using stratification. Pattern Recognit. Lett. 93 (2017)
Nicola Lazzarini, Jaume Bacardit
RGIFE: a ranked guided iterative feature elimination heuristic for the identification of biomarkers. BMC Bioinform. 18 (1) (2017)
Simon Baron, Nicola Lazzarini, Jaume Bacardit
Characterising the Influence of Rule-Based Knowledge Representations in Biological Knowledge Extraction from Transcriptomics Data. EvoApplications (1) (2017)
Nicola Lazzarini, Pawel Widera, Stuart Williamson, Rakesh Heer, Natalio Krasnogor, Jaume Bacardit
Functional networks inference from rule-based machine learning models. BioData Min. 9 (2016)
María A. Franco, Jaume Bacardit
Large-scale experimental evaluation of GPU strategies for evolutionary machine learning. Inf. Sci. 330 (2016)
Pablo David Gutiérrez, Miguel Lastra, Jaume Bacardit, José Manuel Benítez, Francisco Herrera
GPU-SME-kNN: Scalable and memory efficient kNN and lazy learning using GPUs. Inf. Sci. 373 (2016)
María Martínez-Ballesteros, Jaume Bacardit, Alicia Troncoso Lora, José C. Riquelme
Enhancing the scalability of a genetic algorithm to discover quantitative association rules in large-scale datasets. Integr. Comput. Aided Eng. 22 (1) (2015)
Isaac Triguero, Daniel Peralta, Jaume Bacardit, Salvador García, Francisco Herrera
MRPR: A MapReduce solution for prototype reduction in big data classification. Neurocomputing 150 (2015)
Isaac Triguero, Sara del Río, Victoria López, Jaume Bacardit, José Manuel Benítez, Francisco Herrera
ROSEFW-RF: The winner algorithm for the ECBDL'14 big data competition: An extremely imbalanced big data bioinformatics problem. Knowl. Based Syst. 87 (2015)
Isaac Triguero, Daniel Peralta, Jaume Bacardit, Salvador García, Francisco Herrera
A combined MapReduce-windowing two-level parallel scheme for evolutionary prototype generation. IEEE Congress on Evolutionary Computation (2014)
Alvaro Garcia-Piquer, Albert Fornells, Jaume Bacardit, Albert Orriols-Puig, Elisabet Golobardes
Large-Scale Experimental Evaluation of Cluster Representations for Multiobjective Evolutionary Clustering. IEEE Trans. Evol. Comput. 18 (1) (2014)
Jaume Bacardit, Pawel Widera, Nicola Lazzarini, Natalio Krasnogor
Hard Data Analytics Problems Make for Better Data Analysis Algorithms: Bioinformatics as an Example. Big Data 2 (3) (2014)
Jaume Bacardit, Xavier Llorà
Large scale data mining using genetics-based machine learning. GECCO (Companion) (2013)
Jaume Bacardit, Xavier Llorà
Large-scale data mining using genetics-based machine learning. WIREs Data Mining Knowl. Discov. 3 (1) (2013)
Dan Andrei Calian, Jaume Bacardit
Integrating memetic search into the BioHEL evolutionary learning system for large-scale datasets. Memetic Comput. 5 (2) (2013)
Alfonso E. Márquez Chamorro, Federico Divina, Jaume Bacardit, Jesús S. Aguilar-Ruiz
An efficient decision rule-based system for the protein residue-residue contact prediction. IEEE Congress on Evolutionary Computation (2013)
María A. Franco, Natalio Krasnogor, Jaume Bacardit
GAssist vs. BioHEL: critical assessment of two paradigms of genetics-based machine learning. Soft Comput. 17 (6) (2013)
María A. Franco, Natalio Krasnogor, Jaume Bacardit
Analysing BioHEL using challenging boolean functions. Evol. Intell. 5 (2) (2012)
Jaume Bacardit, Xavier Llorà
Large scale data mining using genetics-based machine learning. GECCO (Companion) (2012)
María A. Franco, Natalio Krasnogor, Jaume Bacardit
Post-processing operators for decision lists. GECCO (2012)
Alfonso E. Márquez Chamorro, Federico Divina, Jesús S. Aguilar-Ruiz, Jaume Bacardit, Gualberto Asencio-Cortés, Cosme Ernesto Santiesteban-Toca
A NSGA-II Algorithm for the Residue-Residue Contact Prediction. EvoBIO (2012)
Jaume Bacardit, Pawel Widera, Alfonso E. Márquez Chamorro, Federico Divina, Jesús S. Aguilar-Ruiz, Natalio Krasnogor
Contact map prediction using a large-scale ensemble of rule sets and the fusion of multiple predicted structural features. Bioinform. 28 (19) (2012)
Jaume Bacardit, Xavier Llorà
Large scale data mining using genetics-based machine learning. GECCO (Companion) (2011)
María A. Franco, Natalio Krasnogor, Jaume Bacardit
Modelling the initialisation stage of the ALKR representation for discrete domains and GABIL encoding. GECCO (2011)
Robert Elliott Smith, Max Kun Jiang, Jaume Bacardit, Michael Stout, Natalio Krasnogor, Jonathan D. Hirst
A learning classifier system with mutual-information-based fitness. Evol. Intell. 3 (1) (2010)
Jaume Bacardit, Xavier Llorà
Guest Editorial: Thematic Issue on 'Metaheuristics for large scale data mining'. Memetic Comput. 2 (3) (2010)
María A. Franco, Natalio Krasnogor, Jaume Bacardit
Speeding up the evaluation of evolutionary learning systems using GPGPUs. GECCO (2010)
María A. Franco, Natalio Krasnogor, Jaume Bacardit
Analysing bioHEL using challenging boolean functions. GECCO (Companion) (2010)
Pawel Widera, Jaume Bacardit, Natalio Krasnogor, Carlos García-Martínez, Manuel Lozano
Evolutionary symbolic discovery for bioinformatics, systems and synthetic biology. GECCO (Companion) (2010)
Jaume Bacardit, Xavier Llorà
Large scale data mining using genetics-based machine learning. GECCO (Companion) (2009)
Jaume Bacardit, Edmund K. Burke, Natalio Krasnogor
Improving the scalability of rule-based evolutionary learning. Memetic Comput. 1 (1) (2009)
Jaume Bacardit, Natalio Krasnogor
A mixed discrete-continuous attribute list representation for large scale classification domains. GECCO (2009)
Michael Stout, Jaume Bacardit, Jonathan D. Hirst, Robert Elliott Smith, Natalio Krasnogor
Prediction of topological contacts in proteins using learning classifier systems. Soft Comput. 13 (3) (2009)
Jesús Alcalá-Fdez, Luciano Sánchez, Salvador García, María José del Jesus, Sebastián Ventura, Josep Maria Garrell i Guiu, José Otero, Cristóbal Romero, Jaume Bacardit, Víctor M. Rivas, Juan Carlos Fernández, Francisco Herrera
KEEL: a software tool to assess evolutionary algorithms for data mining problems. Soft Comput. 13 (3) (2009)
Jaume Bacardit, Natalio Krasnogor
Performance and Efficiency of Memetic Pittsburgh Learning Classifier Systems. Evol. Comput. 17 (3) (2009)
Jaume Bacardit, Michael Stout, Jonathan D. Hirst, Alfonso Valencia, Robert Elliott Smith, Natalio Krasnogor
Automated Alphabet Reduction for Protein Datasets. BMC Bioinform. 10 (2009)
Maximiliano Tabacman, Natalio Krasnogor, Jaume Bacardit, Irene Loiseau
Learning classifier systems for optimisation problems: a case study on fractal travelling salesman problem. GECCO (Companion) (2008)
Michael Stout, Jaume Bacardit, Jonathan D. Hirst, Natalio Krasnogor
Prediction of recursive convex hull class assignments for protein residues. Bioinform. 24 (7) (2008)
Jaume Bacardit, Natalio Krasnogor
Fast rule representation for continuous attributes in genetics-based machine learning. GECCO (2008)
Jaume Bacardit, Michael Stout, Jonathan D. Hirst, Kumara Sastry, Xavier Llorà, Natalio Krasnogor
Automated alphabet reduction method with evolutionary algorithms for protein structure prediction. GECCO (2007)
Jaume Bacardit, Ester Bernadó-Mansilla, Martin V. Butz
Learning Classifier Systems: Looking Back and Glimpsing Ahead. IWLCS (2007)
Jaume Bacardit, Natalio Krasnogor
Empirical Evaluation of Ensemble Techniques for a Pittsburgh Learning Classifier System. IWLCS (2007)
Michael Stout, Jaume Bacardit, Jonathan D. Hirst, Natalio Krasnogor, Jacek Blazewicz
From HP Lattice Models to Real Proteins: Coordination Number Prediction Using Learning Classifier Systems. EvoWorkshops (2006)
Jaume Bacardit, Michael Stout, Natalio Krasnogor, Jonathan D. Hirst, Jacek Blazewicz
Coordination number prediction using learning classifier systems: performance and interpretability. GECCO (2006)
Jaume Bacardit, Natalio Krasnogor
Smart crossover operator with multiple parents for a Pittsburgh learning classifier system. GECCO (2006)
Jaume Bacardit
Analysis of the initialization stage of a Pittsburgh approach learning classifier system. GECCO (2005)
Jaume Bacardit, Martin V. Butz
Data Mining in Learning Classifier Systems: Comparing XCS with GAssist. IWLCS (2005)
Jaume Bacardit, David E. Goldberg, Martin V. Butz
Improving the Performance of a Pittsburgh Learning Classifier System Using a Default Rule. IWLCS (2005)
Jaume Bacardit, Josep Maria Garrell i Guiu
Bloat Control and Generalization Pressure Using the Minimum Description Length Principle for a Pittsburgh Approach Learning Classifier System. IWLCS (2005)
Jesús S. Aguilar-Ruiz, Jaume Bacardit, Federico Divina
Experimental Evaluation of Discretization Schemes for Rule Induction. GECCO (1) (2004)
Jaume Bacardit, David E. Goldberg, Martin V. Butz, Xavier Llorà, Josep Maria Garrell i Guiu
Speeding-Up Pittsburgh Learning Classifier Systems: Modeling Time and Accuracy. PPSN (2004)
Jaume Bacardit, Josep Maria Garrell i Guiu
Analysis and Improvements of the Adaptive Discretization Intervals Knowledge Representation. GECCO (2) (2004)
Jaume Bacardit, Josep Maria Garrell i Guiu
Evolving Multiple Discretizations with Adaptive Intervals for a Pittsburgh Rule-Based Learning Classifier System. GECCO (2003)
Jaume Bacardit, Josep Maria Garrell i Guiu
Evolution of Multi-adaptive Discretization Intervals for a Rule-Based Genetic Learning System. IBERAMIA (2002)
Jaume Bacardit, Josep Maria Garrell i Guiu
Evolution Of Adaptive Discretization Intervals For A Rule-based Genetic Learning System. GECCO (2002)
Jaume Bacardit, Josep Maria Garrell i Guiu
The Role of Interval Initialization in a GBML System with Rule Representation and Adaptive Discrete Intervals. CCIA (2002)