Jaume Bacardit Vis

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28EEJaume Bacardit, Natalio Krasnogor: A mixed discrete-continuous attribute list representation for large scale classification domains. GECCO 2009: 1155-1162
27EEJaume Bacardit, Xavier Llorà: Large scale data mining using genetics-based machine learning. GECCO (Companion) 2009: 3381-3412
26EEJaume Bacardit, Michael Stout, Jonathan D. Hirst, Alfonso Valencia, Robert Elliott Smith, Natalio Krasnogor: Automated Alphabet Reduction for Protein Datasets. BMC Bioinformatics 10: (2009)
25EEJaume Bacardit, Edmund K. Burke, Natalio Krasnogor: Improving the scalability of rule-based evolutionary learning. Memetic Computing 1(1): 55-67 (2009)
24EEMichael 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)
23EEJesús 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)
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
21EEJaume Bacardit, Natalio Krasnogor: Fast rule representation for continuous attributes in genetics-based machine learning. GECCO 2008: 1421-1422
20EEMaximiliano 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
19EEJaume 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
18EEMichael Stout, Jaume Bacardit, Jonathan D. Hirst, Natalio Krasnogor: Prediction of recursive convex hull class assignments for protein residues. Bioinformatics 24(7): 916-923 (2008)
17EEJaume 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
16EEJaume Bacardit, Ester Bernadó-Mansilla, Martin V. Butz: Learning Classifier Systems: Looking Back and Glimpsing Ahead. IWLCS 2007: 1-21
15EEJaume Bacardit, Natalio Krasnogor: Empirical Evaluation of Ensemble Techniques for a Pittsburgh Learning Classifier System. IWLCS 2007: 255-268
14EEMichael 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
13EEJaume Bacardit, Natalio Krasnogor: Smart crossover operator with multiple parents for a Pittsburgh learning classifier system. GECCO 2006: 1441-1448
12EEJaume Bacardit, Michael Stout, Natalio Krasnogor, Jonathan D. Hirst, Jacek Blazewicz: Coordination number prediction using learning classifier systems: performance and interpretability. GECCO 2006: 247-254
11EEJaume Bacardit: Analysis of the initialization stage of a Pittsburgh approach learning classifier system. GECCO 2005: 1843-1850
10EEJaume Bacardit, Martin V. Butz: Data Mining in Learning Classifier Systems: Comparing XCS with GAssist. IWLCS 2005: 282-290
9EEJaume Bacardit, David E. Goldberg, Martin V. Butz: Improving the Performance of a Pittsburgh Learning Classifier System Using a Default Rule. IWLCS 2005: 291-307
8EEJaume 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
7EEJesús S. Aguilar-Ruiz, Jaume Bacardit, Federico Divina: Experimental Evaluation of Discretization Schemes for Rule Induction. GECCO (1) 2004: 828-839
6EEJaume Bacardit, Josep Maria Garrell i Guiu: Analysis and Improvements of the Adaptive Discretization Intervals Knowledge Representation. GECCO (2) 2004: 726-738
5EEJaume 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
4EEJaume Bacardit, Josep Maria Garrell i Guiu: Evolving Multiple Discretizations with Adaptive Intervals for a Pittsburgh Rule-Based Learning Classifier System. GECCO 2003: 1818-1831
3EEJaume 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
1EEJaume Bacardit, Josep Maria Garrell i Guiu: Evolution of Multi-adaptive Discretization Intervals for a Rule-Based Genetic Learning System. IBERAMIA 2002: 350-360

Coauthor Index

1Jesús S. Aguilar-Ruiz [7]
2Jesús Alcalá-Fdez [23]
3Ester Bernadó-Mansilla (Ester Bernadó i Mansilla) [16] [22]
4Jacek Blazewicz [12] [14]
5Edmund K. Burke [25]
6Martin V. Butz (Martin Butz) [5] [9] [10] [16] [22]
7Federico Divina [7]
8Juan Carlos Fernández [23]
9Salvador García [23]
10David E. Goldberg [5] [9]
11Josep Maria Garrell i Guiu [1] [2] [3] [4] [5] [6] [8] [23]
12Francisco Herrera [23]
13Jonathan D. Hirst [12] [14] [17] [18] [19] [24] [26]
14María José del Jesús [23]
15Tim Kovacs [22]
16Natalio Krasnogor [12] [13] [14] [15] [17] [18] [19] [20] [21] [24] [25] [26] [28]
17Xavier Llorà [5] [17] [22] [27]
18Irene Loiseau [20]
19José Otero [23]
20Cristóbal Romero [23]
21Luciano Sánchez [23]
22Víctor Manuel Rivas Santos (Víctor M. Rivas) [23]
23Kumara Sastry [17]
24Robert Elliott Smith (Robert E. Smith) [24] [26]
25Michael Stout [12] [14] [17] [18] [19] [24] [26]
26Maximiliano Tabacman [20]
27Keiki Takadama [22]
28Alfonso Valencia [26]
29Sebastián Ventura [23]

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Copyright © Tue Nov 3 08:52:44 2009 by Michael Ley (ley@uni-trier.de)