Jaume Bacardit
Orcid: 0000-0002-2692-7205
According to our database1,
Jaume Bacardit
authored at least 71 papers
between 2002 and 2024.
Collaborative distances:
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Bibliography
2024
ACM Trans. Evol. Learn. Optim., March, 2024
Evolutionary Computation and Explainable AI: A Roadmap to Transparent Intelligent Systems.
CoRR, 2024
2023
Deep learning identification of coronary artery disease from bilateral finger photoplethysmography sensing: A proof-of-concept study.
Biomed. Signal Process. Control., September, 2023
Estimating individual-level pig growth trajectories from group-level weight time series using machine learning.
Comput. Electron. Agric., May, 2023
2022
Qual. Reliab. Eng. Int., 2022
Curating a longitudinal research resource using linked primary care EHR data - a UK Biobank case study.
J. Am. Medical Informatics Assoc., 2022
McCall, David Walker: The intersection of evolutionary computation and explainable AI.
Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Companion Volume, Boston, Massachusetts, USA, July 9, 2022
2021
Computational Strategies for the Identification of a Transcriptional Biomarker Panel to Sense Cellular Growth States in Bacillus subtilis.
Sensors, 2021
CoRR, 2021
2020
CoRR, 2020
Automatic Tuning of Rule-Based Evolutionary Machine Learning via Problem Structure Identification.
IEEE Comput. Intell. Mag., 2020
2019
Qual. Reliab. Eng. Int., 2019
Multi-classifier prediction of knee osteoarthritis progression from incomplete imbalanced longitudinal data.
CoRR, 2019
Automated Individual Pig Localisation, Tracking and Behaviour Metric Extraction Using Deep Learning.
IEEE Access, 2019
Towards Low-Carbon Conferencing: Acceptance of Virtual Conferencing Solutions and Other Sustainability Measures in the ALIFE Community.
Proceedings of the 2019 Conference on Artificial Life, 2019
Proceedings of the 2019 Conference on Artificial Life, 2019
2018
A Combined Deep Learning GRU-Autoencoder for the Early Detection of Respiratory Disease in Pigs Using Multiple Environmental Sensors.
Sensors, 2018
2017
Pattern Recognit. Lett., 2017
RGIFE: a ranked guided iterative feature elimination heuristic for the identification of biomarkers.
BMC Bioinform., 2017
Characterising the Influence of Rule-Based Knowledge Representations in Biological Knowledge Extraction from Transcriptomics Data.
Proceedings of the Applications of Evolutionary Computation - 20th European Conference, 2017
2016
Inf. Sci., 2016
Large-scale experimental evaluation of GPU strategies for evolutionary machine learning.
Inf. Sci., 2016
BioData Min., 2016
2015
ROSEFW-RF: The winner algorithm for the ECBDL'14 big data competition: An extremely imbalanced big data bioinformatics problem.
Knowl. Based Syst., 2015
Neurocomputing, 2015
Enhancing the scalability of a genetic algorithm to discover quantitative association rules in large-scale datasets.
Integr. Comput. Aided Eng., 2015
2014
Large-Scale Experimental Evaluation of Cluster Representations for Multiobjective Evolutionary Clustering.
IEEE Trans. Evol. Comput., 2014
Hard Data Analytics Problems Make for Better Data Analysis Algorithms: Bioinformatics as an Example.
Big Data, 2014
A combined MapReduce-windowing two-level parallel scheme for evolutionary prototype generation.
Proceedings of the IEEE Congress on Evolutionary Computation, 2014
2013
WIREs Data Mining Knowl. Discov., 2013
GAssist vs. BioHEL: critical assessment of two paradigms of genetics-based machine learning.
Soft Comput., 2013
Integrating memetic search into the BioHEL evolutionary learning system for large-scale datasets.
Memetic Comput., 2013
An efficient decision rule-based system for the protein residue-residue contact prediction.
Proceedings of the IEEE Congress on Evolutionary Computation, 2013
2012
Contact map prediction using a large-scale ensemble of rule sets and the fusion of multiple predicted structural features.
Bioinform., 2012
Proceedings of the Genetic and Evolutionary Computation Conference, 2012
Proceedings of the Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, 2012
2011
Modelling the initialisation stage of the ALKR representation for discrete domains and GABIL encoding.
Proceedings of the 13th Annual Genetic and Evolutionary Computation Conference, 2011
2010
Memetic Comput., 2010
Evol. Intell., 2010
Proceedings of the Genetic and Evolutionary Computation Conference, 2010
Proceedings of the Genetic and Evolutionary Computation Conference, 2010
2009
Soft Comput., 2009
Soft Comput., 2009
Evol. Comput., 2009
A mixed discrete-continuous attribute list representation for large scale classification domains.
Proceedings of the Genetic and Evolutionary Computation Conference, 2009
2008
Proceedings of the Learning Classifier Systems in Data Mining, 2008
Bioinform., 2008
Learning classifier systems for optimisation problems: a case study on fractal travelling salesman problem.
Proceedings of the Genetic and Evolutionary Computation Conference, 2008
Fast rule representation for continuous attributes in genetics-based machine learning.
Proceedings of the Genetic and Evolutionary Computation Conference, 2008
2007
Empirical Evaluation of Ensemble Techniques for a Pittsburgh Learning Classifier System.
Proceedings of the Learning Classifier Systems, 2007
Proceedings of the Learning Classifier Systems, 2007
Automated alphabet reduction method with evolutionary algorithms for protein structure prediction.
Proceedings of the Genetic and Evolutionary Computation Conference, 2007
2006
Coordination number prediction using learning classifier systems: performance and interpretability.
Proceedings of the Genetic and Evolutionary Computation Conference, 2006
Smart crossover operator with multiple parents for a Pittsburgh learning classifier system.
Proceedings of the Genetic and Evolutionary Computation Conference, 2006
From HP Lattice Models to Real Proteins: Coordination Number Prediction Using Learning Classifier Systems.
Proceedings of the Applications of Evolutionary Computing, 2006
2005
Improving the Performance of a Pittsburgh Learning Classifier System Using a Default Rule.
Proceedings of the Learning Classifier Systems, International Workshops, 2005
Bloat Control and Generalization Pressure Using the Minimum Description Length Principle for a Pittsburgh Approach Learning Classifier System.
Proceedings of the Learning Classifier Systems, International Workshops, 2005
Proceedings of the Learning Classifier Systems, International Workshops, 2005
Analysis of the initialization stage of a Pittsburgh approach learning classifier system.
Proceedings of the Genetic and Evolutionary Computation Conference, 2005
2004
Proceedings of the Parallel Problem Solving from Nature, 2004
Analysis and Improvements of the Adaptive Discretization Intervals Knowledge Representation.
Proceedings of the Genetic and Evolutionary Computation, 2004
Proceedings of the Genetic and Evolutionary Computation, 2004
2003
Evolving Multiple Discretizations with Adaptive Intervals for a Pittsburgh Rule-Based Learning Classifier System.
Proceedings of the Genetic and Evolutionary Computation, 2003
2002
Evolution of Multi-adaptive Discretization Intervals for a Rule-Based Genetic Learning System.
Proceedings of the Advances in Artificial Intelligence, 2002
Evolution Of Adaptive Discretization Intervals For A Rule-based Genetic Learning System.
Proceedings of the GECCO 2002: Proceedings of the Genetic and Evolutionary Computation Conference, 2002
The Role of Interval Initialization in a GBML System with Rule Representation and Adaptive Discrete Intervals.
Proceedings of the Topics in Artificial Intelligence, 5th Catalonian Conference on AI, 2002