![]() | ![]() |
| 2012 | ||
|---|---|---|
| 38 | 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: 234-244 | |
| 2011 | ||
| 37 | María A. Franco, Natalio Krasnogor, Jaume Bacardit: Modelling the initialisation stage of the ALKR representation for discrete domains and GABIL encoding. GECCO 2011: 1291-1298 | |
| 36 | Jaume Bacardit, Xavier Llorà: Large scale data mining using genetics-based machine learning. GECCO (Companion) 2011: 1285-1310 | |
| 2010 | ||
| 35 | Jaume Bacardit, Will N. Browne, Jan Drugowitsch, Ester Bernadó-Mansilla, Martin V. Butz: Learning Classifier Systems - 11th International Workshop, IWLCS 2008, Atlanta, GA, USA, July 13, 2008, and 12th International Workshop, IWLCS 2009, Montreal, QC, Canada, July 9, 2009, Revised Selected Papers Springer 2010 | |
| 34 | María A. Franco, Natalio Krasnogor, Jaume Bacardit: Speeding up the evaluation of evolutionary learning systems using GPGPUs. GECCO 2010: 1039-1046 | |
| 33 | María A. Franco, Natalio Krasnogor, Jaume Bacardit: Analysing bioHEL using challenging boolean functions. GECCO (Companion) 2010: 1855-1862 | |
| 32 | Pawel Widera, Jaume Bacardit, Natalio Krasnogor, Carlos García-Martínez, Manuel Lozano: Evolutionary symbolic discovery for bioinformatics, systems and synthetic biology. GECCO (Companion) 2010: 1991-1998 | |
| 31 | Robert Elliott Smith, Max Kun Jiang, Jaume Bacardit, Michael Stout, Natalio Krasnogor, Jonathan D. Hirst: A learning classifier system with mutual-information-based fitness. Evolutionary Intelligence 3(1): 31-50 (2010) | |
| 30 | Jaume Bacardit, Xavier Llorà: Guest Editorial: Thematic Issue on 'Metaheuristics for large scale data mining'. Memetic Computing 2(3): 163-164 (2010) | |
| 2009 | ||
| 29 | Jaume Bacardit, Natalio Krasnogor: A mixed discrete-continuous attribute list representation for large scale classification domains. GECCO 2009: 1155-1162 | |
| 28 | Jaume Bacardit, Xavier Llorà: Large scale data mining using genetics-based machine learning. GECCO (Companion) 2009: 3381-3412 | |
| 27 | Jaume Bacardit, Michael Stout, Jonathan D. Hirst, Alfonso Valencia, Robert Elliott Smith, Natalio Krasnogor: Automated Alphabet Reduction for Protein Datasets. BMC Bioinformatics 10: (2009) | |
| 26 | Jaume Bacardit, Natalio Krasnogor: Performance and Efficiency of Memetic Pittsburgh Learning Classifier Systems. Evolutionary Computation 17(3): 307-342 (2009) | |
| 25 | Jaume Bacardit, Edmund K. Burke, Natalio Krasnogor: Improving the scalability of rule-based evolutionary learning. Memetic Computing 1(1): 55-67 (2009) | |
| 24 | 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): 245-258 (2009) | |
| 23 | Jesús Alcalá-Fdez, Luciano Sánchez, Salvador García, María José del Jesús, 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): 307-318 (2009) | |
| 2008 | ||
| 22 | Jaume Bacardit, Ester Bernadó-Mansilla, Martin V. Butz, Tim Kovacs, Xavier Llorà, Keiki Takadama: Learning Classifier Systems, 10th International Workshop, IWLCS 2006, Seattle, MA, USA, July 8, 2006 and 11th International Workshop, IWLCS 2007, London, UK, July 8, 2007, Revised Selected Papers Springer 2008 | |
| 21 | Jaume Bacardit, Natalio Krasnogor: Fast rule representation for continuous attributes in genetics-based machine learning. GECCO 2008: 1421-1422 | |
| 20 | 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: 2039-2046 | |
| 19 | Jaume Bacardit, Michael Stout, Jonathan D. Hirst, Natalio Krasnogor: Data Mining in Proteomics with Learning Classifier Systems. Learning Classifier Systems in Data Mining 2008: 17-46 | |
| 18 | Michael Stout, Jaume Bacardit, Jonathan D. Hirst, Natalio Krasnogor: Prediction of recursive convex hull class assignments for protein residues. Bioinformatics 24(7): 916-923 (2008) | |
| 2007 | ||
| 17 | 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: 346-353 | |
| 16 | Jaume Bacardit, Ester Bernadó-Mansilla, Martin V. Butz: Learning Classifier Systems: Looking Back and Glimpsing Ahead. IWLCS 2007: 1-21 | |
| 15 | Jaume Bacardit, Natalio Krasnogor: Empirical Evaluation of Ensemble Techniques for a Pittsburgh Learning Classifier System. IWLCS 2007: 255-268 | |
| 2006 | ||
| 14 | 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: 208-220 | |
| 13 | Jaume Bacardit, Natalio Krasnogor: Smart crossover operator with multiple parents for a Pittsburgh learning classifier system. GECCO 2006: 1441-1448 | |
| 12 | Jaume Bacardit, Michael Stout, Natalio Krasnogor, Jonathan D. Hirst, Jacek Blazewicz: Coordination number prediction using learning classifier systems: performance and interpretability. GECCO 2006: 247-254 | |
| 2005 | ||
| 11 | Jaume Bacardit: Analysis of the initialization stage of a Pittsburgh approach learning classifier system. GECCO 2005: 1843-1850 | |
| 10 | Jaume Bacardit, Martin V. Butz: Data Mining in Learning Classifier Systems: Comparing XCS with GAssist. IWLCS 2005: 282-290 | |
| 9 | Jaume Bacardit, David E. Goldberg, Martin V. Butz: Improving the Performance of a Pittsburgh Learning Classifier System Using a Default Rule. IWLCS 2005: 291-307 | |
| 8 | 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: 59-79 | |
| 2004 | ||
| 7 | Jesús S. Aguilar-Ruiz, Jaume Bacardit, Federico Divina: Experimental Evaluation of Discretization Schemes for Rule Induction. GECCO (1) 2004: 828-839 | |
| 6 | Jaume Bacardit, Josep Maria Garrell i Guiu: Analysis and Improvements of the Adaptive Discretization Intervals Knowledge Representation. GECCO (2) 2004: 726-738 | |
| 5 | 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: 1021-1031 | |
| 2003 | ||
| 4 | Jaume Bacardit, Josep Maria Garrell i Guiu: Evolving Multiple Discretizations with Adaptive Intervals for a Pittsburgh Rule-Based Learning Classifier System. GECCO 2003: 1818-1831 | |
| 2002 | ||
| 3 | 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: 184-195 | |
| 2 | Jaume Bacardit, Josep Maria Garrell i Guiu: Evolution Of Adaptive Discretization Intervals For A Rule-based Genetic Learning System. GECCO 2002: 677 | |
| 1 | Jaume Bacardit, Josep Maria Garrell i Guiu: Evolution of Multi-adaptive Discretization Intervals for a Rule-Based Genetic Learning System. IBERAMIA 2002: 350-360 | |
Colors in the list of coauthors
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