Jaume Bacardit

According to our database1, Jaume Bacardit authored at least 55 papers between 2002 and 2018.

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Bibliography

2018
A Combined Deep Learning GRU-Autoencoder for the Early Detection of Respiratory Disease in Pigs Using Multiple Environmental Sensors.
Sensors, 2018

2017
Scaling-up multiobjective evolutionary clustering algorithms using stratification.
Pattern Recognition Letters, 2017

RGIFE: a ranked guided iterative feature elimination heuristic for the identification of biomarkers.
BMC Bioinformatics, 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
GPU-SME-kNN: Scalable and memory efficient kNN and lazy learning using GPUs.
Inf. Sci., 2016

Large-scale experimental evaluation of GPU strategies for evolutionary machine learning.
Inf. Sci., 2016

Functional networks inference from rule-based machine learning models.
BioData Mining, 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

MRPR: A MapReduce solution for prototype reduction in big data classification.
Neurocomputing, 2015

Enhancing the scalability of a genetic algorithm to discover quantitative association rules in large-scale datasets.
Integrated Computer-Aided Engineering, 2015

2014
Large-Scale Experimental Evaluation of Cluster Representations for Multiobjective Evolutionary Clustering.
IEEE Trans. Evolutionary Computation, 2014

A combined MapReduce-windowing two-level parallel scheme for evolutionary prototype generation.
Proceedings of the IEEE Congress on Evolutionary Computation, 2014

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 Computing, 2013

Large scale data mining using genetics-based machine learning.
Proceedings of the Genetic and Evolutionary Computation Conference, 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.
Bioinformatics, 2012

Post-processing operators for decision lists.
Proceedings of the Genetic and Evolutionary Computation Conference, 2012

Large scale data mining using genetics-based machine learning.
Proceedings of the Genetic and Evolutionary Computation Conference, 2012

A NSGA-II Algorithm for the Residue-Residue Contact Prediction.
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

Large scale data mining using genetics-based machine learning.
Proceedings of the 13th Annual Genetic and Evolutionary Computation Conference, 2011

2010
Guest Editorial: Thematic Issue on 'Metaheuristics for large scale data mining'.
Memetic Computing, 2010

A learning classifier system with mutual-information-based fitness.
Evolutionary Intelligence, 2010

Evolutionary symbolic discovery for bioinformatics, systems and synthetic biology.
Proceedings of the Genetic and Evolutionary Computation Conference, 2010

Analysing bioHEL using challenging boolean functions.
Proceedings of the Genetic and Evolutionary Computation Conference, 2010

Speeding up the evaluation of evolutionary learning systems using GPGPUs.
Proceedings of the Genetic and Evolutionary Computation Conference, 2010

2009
Prediction of topological contacts in proteins using learning classifier systems.
Soft Comput., 2009

KEEL: a software tool to assess evolutionary algorithms for data mining problems.
Soft Comput., 2009

Improving the scalability of rule-based evolutionary learning.
Memetic Computing, 2009

Performance and Efficiency of Memetic Pittsburgh Learning Classifier Systems.
Evolutionary Computation, 2009

Automated Alphabet Reduction for Protein Datasets.
BMC Bioinformatics, 2009

Large scale data mining using genetics-based machine learning.
Proceedings of the Genetic and Evolutionary Computation Conference, 2009

A mixed discrete-continuous attribute list representation for large scale classification domains.
Proceedings of the Genetic and Evolutionary Computation Conference, 2009

2008
Data Mining in Proteomics with Learning Classifier Systems.
Proceedings of the Learning Classifier Systems in Data Mining, 2008

Prediction of recursive convex hull class assignments for protein residues.
Bioinformatics, 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

Learning Classifier Systems: Looking Back and Glimpsing Ahead.
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

Data Mining in Learning Classifier Systems: Comparing XCS with GAssist.
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
Speeding-Up Pittsburgh Learning Classifier Systems: Modeling Time and Accuracy.
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

Experimental Evaluation of Discretization Schemes for Rule Induction.
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


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