Pedro Larrañaga

Pedro Larranaga is Full Professor in Computer Science and Artiﬁcial Intelligence at the Technical University of Madrid (UPM) since 2007. He received the MSc degree in mathematics (statistics) from the University of Valladolid and the PhD degree in computer science from the University of the Basque Country (“excellence award”). Before moving to UPM, his academic career has been developed at the University of the Basque Country (UPV-EHU) at several faculty ranks: Assistant Professor (1985-1998), Associate Professor (1998-2004) and Full Professor (2004-2007). He earned the habilitation qualiﬁcation for Full Professor in 2003.

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Curriculum vitae

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Journal publications

Year: 2013

Armañanzas, R., Bielza, C., Chaudhuri, K. R., Martínez-Martín, P. & Larrañaga, P. (2013). Unveiling relevant non-motor Parkinson's disease severity symptoms using a machine learning approach. Artificial Intelligence in Medicine. In press. BibTex

Armañanzas, R., Alonso-Nanclares, L., DeFelipe-Oroquieta, J., Kastanauskaite, A., de Sola, R.G., DeFelipe, J., Bielza, C. & Larrañaga, P. (2013). Machine learning approach for the outcome prediction of temporal lobe epilepsy surgery. PLoS ONE. In press. BibTex

Borchani, H., Bielza, C., Toro, C., Larrañaga, P. (2013). Predicting human immunodeficiency virus inhibitors using multi-dimensional Bayesian network classifiers. Artificial Intelligence in Medicine. In press. BibTex

DeFelipe, J., Lopez-Cruz, P.L., Benavides-Piccione, R., Bielza, C., Larrañaga, P. & et al. (2013). New insights into the classification and nomenclature of cortical GABAergic interneurons. Nature Reviews Neuroscience. In press. BibTex

García-Torres, M., Armañanzas, R., Bielza, C. & Larrañaga, P. (2013). Comparison of metaheuristic strategies for peakbin selection in proteomic mass spectrometry data. Information Sciences, 222, 229-246. BibTex

Ibañez, A., Bielza, C. & Larrañaga, P. (2013). Análisis de la actividad científica de las universidades públicas españolas en el área de las tecnologías informáticas. Revista Española de Documentación Científica, 36(1):e002. BibTex

Ibañez, A., Larrañaga, P. & Bielza, C. (2013). Cluster methods for assessing research performance: exploring Spanish computer science. Scientometrics. In press. BibTex

Karshenas H., Santana R., Bielza C., Larrañaga P. (2013). Regularized continuous estimation of distribution algorithms. Applied Soft Computing 13(5): 2412-2432

Larrañaga, P., Karshenas, H., Bielza, C., Santana, R. (2013). A review on evolutionary algorithms in Bayesian network learning and inference tasks. Information Sciences, 233, 109-125. BibTex

López-Cruz, P.L., Larrañaga, P., DeFelipe, J., Bielza, C. (2013). Bayesian network modeling of the consensus between experts: An application to neuron classification. International Journal of Approximate Reasoning. In press. BibTex

Merchán-Pérez, A., Rodríguez, R., González, S., Robles, V., DeFelipe, J., Larrañaga, P., Bielza, C. (2013). Three-dimensional spatial distribution of synapses in the neocortex: A dual-beam electron microscopy study. Cerebral Cortex. In press. BibTex

Santana, R., Armañanzas, R., Bielza, C. & Larrañaga, P. (2013). Network measures for information extraction in evolutionary algorithms. International Journal of Computational Intelligence Systems. In press. BibTex

Vidaurre, D., Bielza, C., Larrañaga, P. (2013). Classification of neural signals from sparse autoregressive features. Neurocomputing, 111, 21-26. BibTex

Vidaurre, D., Bielza, C., Larrañaga, P. (2013). Sparse regularized local regression. Computational Statistics and Data Analysis, 62, 122-135.

Vidaurre, D., Bielza, C., Larrañaga, P. (2013). A survey on L1-regularization for statistics and machine learning. International Statistical Review. In press.
Vidaurre, D. Bielza, C., Larrañaga, P. (2013). An L1-regularized naive Bayes-inspired classifier for discarding redundant predictors. International Journal on Artificial Intelligence Tools. In press.

Year: 2012

Armañanzas, R., Larrañaga, P. & Bielza, B. (2012). Ensemble transcript interaction networks: A case study on Alzheimer’s disease. Computer Methods and Programs in Biomedicine, in press
Borchani, H., Bielza, C., Martínez-Martín, P. & Larrañaga, P. (2012). Markov blanket-based approach for learning multi-dimensional Bayesian network classifiers: An application to predict the European Quality of Life-5Dimensions (EQ-5D) from the 39-item Parkinson's Disease Questionnaire (PDQ-39). Journal of Biomedical Informatics, accepted for publication. BibTex
Calvo, B., Inza, I., Larrañaga, P. & Lozano, J.A. (2012). Wrapper positive Bayesian network classifiers. Knowledge and Information Systems, 33(3), 631-654. BibTex
Dueñas, M., Santos, M., Aranda, J.F., Bielza, C., Martínez-Cruz, A.B., Lorz, C., Taron, M., Ciruelos, E.M., Rodríguez-Peralto, J.L., Martín, M. et al. (2012). Mouse p53-deficient cancer models as platforms for obtaining genomic predictors of human cancer clinical outcomes. PLoS One, accepted for publication. BibTex

Garcia-Bilbao, A., Armañanzas, R., Ispizua, Z., Calvo, B., Alonso-Varona, A., Inza, I., Larrañaga, P., López-Vivanco, G., Suárez-Merino, B. & Betanzos, M. (2012). Identiﬁcation of a biomarker panel for colorectal cancer diagnosis. BMC Cancer, in press
Guerra, L., Robles, V., Bielza, C. & Larrañaga, P. (2012). A comparison of cluster quality indices using outliers and noise. Intelligent Data Analysis, 16, 703-715. BibTex

Ibañez, A., Bielza, C. & Larrañaga, P. (2012). Analysis of scientific activity in Spanish public universities in the area of computer science. Revista Española de Documentación Científica, In press. BibTex

Karshenas, H., Santana, R., Bielza, C. & Larrañaga, P (2012). Continuous Estimation of Distribution Algorithms Based on Factorized Gaussian Markov Networks. In Adaptation, Learning & Optimization. series Vol. 14 (editors), Markov Networks in Evolutionary Algorithms. Springer. BibTex

Lopez-Cruz, P.L., Bielza, C. & Larrañaga, P (2012). Learning mixtures of polynomials from data using B-spline interpolation. In Sixth European Workshop on Probabilistic Graphical Models (PGM 2012). In press. BibTex

Lopez-Cruz, P.L., Larrañaga, P., DeFelipe, J. & Bielza, C. (2012). Bayesian network modeling of the consensus between experts: An application to neuron classification. International Journal of Approximate Reasoning, in press. BibTex

Morales, D., Vives-Gilabert, Y., Gómez-Ansón, B., Bengoetxea, E., Larrañaga, P., Bielza, C., Pagonabarraga, J., Kulisevsky, J., Corcuera-Solano, I. & Delfino, M. (2012). Predicting dementia development in Parkinson's disease using Bayesian network classifiers. Psychiatry Research: NeuroImaging, accepted for publication. BibTex

Santana, R., Bielza, C. & Larrañaga, P. (2012). Regularized logistic regression and multi-objective variable selection for classifying MEG data. Biological Cybernetics, In press. BibTex

Santana, R., Bielza, C. & Larrañaga, P (2012). Maximizing the number of polychronous groups in spiking networks. InCompanion Material Proceedings of the 14th Annual Genetic and Evolutionary Computation Conference (GECCO-2012), pages 1499-1500. ACM Digital Library. BibTex

Santana, R., Bielza, C. & Larrañaga, P. (2012). Conductance interaction identification by means of Boltzmann distribution and mutual information analysis in conductance-based neuron models. BMC Neuroscience, accepted for publication. BibTex

Vidaurre, D., Bielza, C. & Larrañaga, P. (2012). Forward stagewise naive Bayes. Progress in Artiﬁcial Intelligence, in press.

Vidaurre, D., Rodríguez, E.E., Rudomin, P., Bielza, C. & Larrañaga, P. (2012). A new feature extraction method for signal classification applied to cat spinal cord signals. Journal of Neural Engineering, in press. BibTex

Year: 2011

García-Torres, M., Armañanzas, R., Bielza, C. & Larrañaga, P. (2011). Comparison of metaheuristic strategies for peakbin selection in proteomic mass spectrometry data. Information Sciences, In press.
Lopez-Cruz, P.L., Bielza, C., Larrañaga, P., Benavides-Piccione, R. & DeFelipe, J. (2011). Models and simulation of 3D neuronal dendritic trees using Bayesian networks. Neuroinformatics, 9(4), 347-369.
Armañanzas, R., Saeys, Y., Inza, I., Garca-Torres, M., Bielza, C., van de Peer, Y. & Larrañaga, P. (2011). Peakbin selection in mass spectrometry data using a consensus approach with estimation of distribution algorithms.IEEE/ACM Transactions on Computational Biology and Bioinformatics, 8(3), 760-774.
Bengoetxea, E., Larrañaga, P., Bielza, C. & Fernandez del Pozo, J.A. (2011). Optimal Row and Column Ordering to Improve Table Interpretation Using Estimation of Distribution Algorithms. Journal of Heuristics, 17(5), 567-588.
Bielza, C., Li, G. & Larrañaga, P. (2011). Multi-Dimensional Classification with Bayesian Networks. International Journal of Approximate Reasoning, 52, 705-727.
Bielza, C., Robles, V. & Larrañaga, P. (2011). Regularized Logistic Regression without a Penalty Term: An Application to Cancer Classification with Microarray Data. Expert Systems with Applications, 38, 5110-5118.
Borchani, H., Larrañaga, P. & Bielza, C. (2011). Classifying evolving data streams with partially labeled data.Intelligent Data Analysis, 15(5), 655-670
Guerra, L., McGarry, L., Robles, V., Bielza, C., Larrañaga, P. & Yuste, R. (2011). Comparison between Supervised and Unsupervised Classification of Neuronal Cell Types: A Case Study. Developmental Neurobiology, 71(1), 71-82.
Ibañez, A., Larrañaga, P. & Bielza, C. (2011). Using Bayesian networks to discover relationships between bibliometric indices. A case study of computer science and artificial intelligence journals. Scientometrics, 89(2), 523-551.
Larrañaga, P. & Moral, S. (2011). Probabilistic graphical models in artificial intelligence. Applied Soft Computing,11(2), 1511-1528.
Santana, R., Bielza, C. & Larrañaga, P. (2010). Optimizing brain networks topologies using multi-objective evolutionary computation.. Neuroinformatics, 9(1), 3-19
Vidaurre, D., Bielza, C. & Larrañaga, P. (2011). On nonlinearity in neural encoding models applied to the primary visual cortex. Network: Computation in Neural Systems, 22(1-4), 97-125
Vidaurre, D., Bielza, C. & Larrañaga, P. (2011). Lazy lasso for local regression. Computational Statistics, In press.

Year: 2010

Bielza, C., Fernandez del Pozo, J.A., Larrañaga, P. & Bengoetxea, E. (2010). Multidimensional Statistical Analysis of the Parameterization of a Genetic Algorithm for the Optimal Ordering of Tables. Expert Systems with Applications, 37, 804-815.
Cuesta, I., Bielza, C., Cuenca-Estrella, M., Larrañaga, P. & Rodríguez-Tudela, J.L. (2010). Evaluation by Data Mining Techniques of Fluconazole Breakpoints Established by the Clinical and Laboratory Standards Institute (CLSI) and Comparison with those of the European Committee on Antimicrobial Susceptibility Testing (EUCAST). Antimicrobial Agents and Chemotherapy, 54(4), 1541-1546. BibTex
Santana, R., Bielza, C., Larrañaga, P., Lozano, J.A., Echegoyen, C., Mendiburu, A., Armañanzas, R. & Shakya, S. (2010). MATEDA: A Matlab Package for the Implementation and Analysis of Estimation of Distribution Algorithms. Journal of Statistical Software, 35(7), 1-30.
Santana, R., Larrañaga, P. & Lozano, J.A. (2010). Learning factorizations in estimation of distribution algorithms using affinity propagation. Evolutionary Computation, 18(4), 515-546
Vidaurre, D., Bielza, C. & Larrañaga, P. (2010). Learning an L1-regularized Gaussian Bayesian Network in the Equivalence Class Space. IEEE Transactions on Systems, Man and Cybernetics, Part B, 40(5), 1231-1242.
Ibáñez, I., Larrañaga, P., Bielza, C. (2010). Predicen el número de citas que tendrán los artículos cientíﬁcos. Madri+d Noticias (artículo de divulgación) y Plataforma SINC de la FECYT (Servicio de Información y Noticias Cientíﬁcas)

Year: 2009

Armañanzas, R., Calvo, B., Inza, I., López-Hoyos, M., Martínez-Taboada, V., Ucar, E., Bernales, I., Fullaondo, A., Larrañaga, P. & Zubiaga, A.M. (2009). Microarray analysis of autoimmune diseases by machine learning procedures. IEEE Transactions on Information Technology in Biomedicine, 13(3), 341-350.
Bielza, C., Robles, V. & Larrañaga, P. (2009). Estimation of Distribution Algorithms as Logistic Regression Regularizers of Microarray Classifiers. Methods of Information in Medicine, 48(3), 236-241.
Calvo, B., Larrañaga, P. & Lozano, J.A. (2009). Feature subset selection from positive and unlabelled examples. Pattern Recognition Letters, 30, 1027-1036.
Cuesta, I., Bielza, C., Larrañaga, P., Cuenca-Estrella, M., Laguna, F., Rodríguez-Pardo, D. & Almirante, B. (2009). Data Mining Validation of EUCAST Fluconazole Breakpoints Established by the European Committee on Antimicrobial Susceptibility Testing. Antimicrobial Agents and Chemotherapy, 53(7), 2949-2954.
Ibañez, A., Larrañaga, P. & Bielza, C. (2009). Predicting Citation Count of Bioinformatics Papers within Four Years of Publication. Bioinformatics, 25(24), 3303-3309.
Pérez, A., Larrañaga, P. & Inza, I. (2009). Bayesian classifiers based on kernel estimation: Flexible classifiers. International Journal of Approximate Reasoning, 50(2), 341-362.
Romero, T. & Larrañaga, P. (2009). Triangulation of Bayesian networks with recursive estimation of distribution algorithms. International Journal of Approximate Reasoning, 50(3), 472-484.
D. Morales, E. Bengoetxea, P. Larrañaga (2009). Clasiﬁcadores Bayesianos en la selección embrionaria en tratamientos de reproducción asistida. Matematicalia 4, 3.
Lozano, J.A., Zhang Q., Larrañaga P. (2009). Special Issue in Evolutionary Algorithms based on Probabilistic Models. IEEE Transactions on Evolutionary Computation, 13(6), 1197-1198.

Year: 2008

Armañanzas, R., Inza, I., Santana, R., Saeys, Y., Flores, J.L., Lozano, J.A., Van de Peer, Y., Blanco, R., Robles, V., Bielza, C. et al. (2008). A review of estimation of distribution algorithms in bioinformatics. BioData Mining, 1(6).
Armañanzas, R., Inza, I. & Larrañaga, P. (2008). Detecting reliable gene interactions by a hierarchy of Bayesian networks classifiers. Computer Methods and Programs in Biomedicine, 91, 110-121.
Furney, S., Calvo, B., Larrañaga, P., Lozano, J.A. & López-Bigas, N. (2008). Prioritization of candidate cancer genes-an aid to oncogenomic studies. Nucleic Acids Research, , 1-9.
Morales, D., Bengoetxea, E. & Larrañaga, P. (2008). Selection of human embryos for transfer by Bayesian classifiers. Computer in Biology and Medicine, 38, 1177-1186.
Morales, D., Bengoetxea, E., Larrañaga, P., Garca, M., Franco-Iriarte, Y., Fresnada, M. & Merino, M. (2008). Bayesian classification for the selection of in-vitro human embryos using morphological and clinical data. Computer Methods and Programs in Biomedicine, (90), 104-116.
Robles, V., Bielza, C., Larrañaga, P., González, S. & Ohno-Machado, L. (2008). Optimizing Logistic Regression Coefficients for Discrimination and Calibration Using Estimation of Distribution Algorithms. TOP, 16, 345-366.
Santafé, G., Lozano, J.A. & Larrañaga, P. (2008). Inference of population structure using genetic markers and a Bayesian model averaging approach for clustering. Journal of Computational Biology, 15(2), 207-220.
Santana, R., Larrañaga, P. & Lozano, J.A. (2008). Combining variable neighborhood search and estimation of distribution algorithms. Journal of Heuristics, 14, 519-547.
Santana, R., Lozano, J.A. & Larrañaga, P. (2008). Protein folding in simplified models with estimation of distribution algorithms. IEEE Transactions on Evolutionary Computation, 12(4), 418-438.
Zipritia, I., Elorriaga, J., Arruarte, A., Larrañaga, P. & Armañanzas, R. (2008). What is behind a summary evaluation decision?. Behavior Research Methods, 2(40), 597-612.
R. Santana, J. A. Lozano, P. Larrañaga (2008). Research topics in discrete estimation of distribution algorithms. Memetic Computing, 1, 135-54

Year: 2007

Calvo, B., Lozano, J.A. & Larrañaga, P. (2007). Learning Bayesian classifiers from positive and unlabeled examples. Pattern Recognition Letters, 28(16), 2375-2384.
Calvo, B., López-Bigas, N., Furney, S.J., Larrañaga, P. & Lozano, J.A. (2007). A partially supervised approach to dominant and recessive human disease gene prediction. Computer Methods and Programs in Biomedicine, 85(3), 229-237.
Flores, J.L., Inza, I. & Larrañaga, P. (2007). Wrapper discretization by means of estimation of distribution algorithms. Intelligent Data Analysis Journal, 11(5), 525-546.
Miquelez, T., Bengoetxea, E., Mendiburu, A. & Larrañaga, P. (2007). Combining Bayesian classifiers and estimation of distribution algorithms for optimization in continuous domains. Connection Science, 19(4), 297-319.
Saeys, Y., Inza, I. & Larrañaga, P. (2007). A review of feature selection techniques in bioinformatics. Bioinformatics, 23(19), 2507-2517.
Santana, R., Larrañaga, P. & Lozano, J.A. (2007). Side chain placement using estimation of distribution algorithms. Artificial Intelligence in Medicine, 39(1), 49-63.

Year: 2006

Larrañaga, P., Calvo. B., Santana, R., Bielza, C., Galdiano, J., Inza, I., Lozano, J.A., Armañanzas, R., Santafé, G., Pérez, A. et al. (2006). Machine Learning in Bioinformatics. Briefings in Bioinformatics, 17(1), 86-112.
Pérez, A., Larrañaga, P. & Inza, I. (2006). Supervised classification with conditional Gaussian networks: Increasing the structure complexity from naive Bayes. International Journal of Approximate Reasoning, 43, 1-25.
Santafé, G., Lozano, J.A. & Larrañaga, P. (2006). Bayesian model averaging of naive Bayes for clustering. IEEE Transactions on Systems, Man, and Cybernetics, 36(5), 1149-1161.
G. Santafé, J. A. Lozano, P. Larrañaga (2006). Aprendizaje discriminativo de clasiﬁcadores Bayesianos. Inteligencia Artiﬁcial. Revista Iberoamericana de Inteligencia Artiﬁcial 29, 39-47

Year: 2005

Blanco, R., Inza, I., Merino, M., Quiroga, J. & Larrañaga, P. (2005). Feature selection in Bayesian classifiers for the prognosis of survival of cirrhotic patients treated with TIPS. Journal of Biomedical Informatics, 38, 376–388.
Larrañaga, P. & Lozano, J.A. (2005). Special issue on estimation of distribution algorithms. Evolutionary Computation, 13(1), v-vi.
Larrañaga, P., Lozano, J.A., Peña, J.M. & Inza, I. (2005). Special issue on Probabilistic Graphical Models in Classification. Machine Learning, 59, 211-212.
Peña, J.M., Lozano, J.A. & Larrañaga, P. (2005). Globally multimodal problem optimization via an estimation of distribution algorithm based on unsupervised learning of Bayesian networks. Evolutionary Computation, , 43-66.
Roberto, C., Bengoetxea, E., Bloch, I. & Larrañaga, P. (2005). Inexact graph matching for model-based recognition: Evaluation and comparison of optimization algorithms. Pattern Recognition, 38, 2099–2113.

Year: 2004

Blanco, R., Larrañaga, P., Inza, I. & Sierra, B. (2004). Gene selection for cancer classification using wrapper approaches. International Journal of Pattern Recognition and Artificial Intelligence, 18(8), 1373-1390.
Inza, I., Larrañaga, P., Blanco, R. & Cerrolaza, A.J. (2004). Filter versus wrapper gene selection approaches in DNA microarray domains. Artificial Intelligence in Medicine, (31), 91-103.
Miquelez, T., Bengoetxea, E. & Larrañaga, P. (2004). Evolutionary computation based on Bayesian classifiers. International Journal of Applied Mathematics and Computer Science, 14(3), 101–115.
Robles, V., Larrañaga, P., Peña, J.M., Menasalvas, E., Pérez, M.S. & Herves, V. (2004). Bayesian networks as consensed voting system in the construction of a multi–classifier for protein secondary structure prediction. Artificial Intelligence in Medicine, (31), 117–136.
Romero, T., Larrañaga, P. & Sierra, B. (2004). Learning Bayesian networks in the space of orderings with estimation of distribution algorithms. International Journal of Pattern Recognition and Artificial Intelligence, 18(4), 607–625.
Larrañaga, P., Menasalvas, E., Peña. J.M. & Robles, V. (2004). Data mining in genomics and proteomics. Artificial Intelligence in Medicine, (31), iii-iv.
Peña, J.M., Lozano, J.A. & Larrañaga, P. (2004). Unsupersived learning of Bayesian networks via estimation of distribution algorithms: an application to gene expression data clustering. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 12, 63-82
M. Merino, J. Quiroga, I. Inza, P. Larrañaga (2004). Predicción de mortalidad precoz tras TIPS. ¿Es mejorable el MELD score?. Revista de la Sociedad Española de Calidad Asistencial

Year: 2003

Blanco, R., Inza, I. & Larrañaga, P. (2003). Learning Bayesian networks in the space of structures by estimation of distribution algorithms. International Journal of Intelligent Systems, 18, 205-220.
P. Larrañaga, J.A. Lozano, H. Mühlenbein (2003). Algoritmos de estimación de distribuciones en problemas de optimización combinatoria. Inteligencia Artiﬁcial. Revista Iberoamericana de Inteligencia Artiﬁcial, No. 19, Vol. 2, 149-168

Year: 2002

Bengoetxea, E., Larrañaga, P., Bloch, I., Perchant, A. & Boeres, C. (2002). Inexact graph matching by means of estimation of distribution algorithms. Pattern Recognition, 35(12), 2867–2880.
González, C., Lozano, J.A. & Larrañaga, P. (2002). Mathematical modelling of UMDAc algorithm with tournament selection. Behaviour on linear and quadratic functions. International Journal of Approximate Reasoning, 31, 313–340.
Inza, I., Sierra, B., Blanco, R. & Larrañaga, P. (2002). Gene selection by sequential search wrapper approaches in microarray cancer class prediction. Journal of Intelligent and Fuzzy Systems, 12(1), 25-33.
Larrañaga, P. & Lozano, J.A. (2002). Synergies between evolutionary computation and probabilistic graphical models. International Journal of Approximate Reasoning, 31, 155–156.
Peña, J.M., Lozano, J.A. & Larrañaga, P. (2002). Learning recursive Bayesian multinets for clustering by means of constructive induction. Machine Learning, 47, 63-89.

Year: 2001

Inza, I., Larrañaga, P. & Sierra, B. (2001). Feature subset selection by Bayesian networks: a comparison with genetic and sequential algorithms. International Journal of Approximate Reasoning, 27, 143–164.
Inza, I., Merino, M., Larrañaga, P., Quiroga, J., Sierra, B. & Girala, M. (2001). Feature subset selection by genetic algorithms and estimation of distribution algorithms. A case study in the survival of cirrhotic patients treated with TIPS. Artificial Intelligence in Medicine, 23(2), 187–205.
Peña. J.M., Lozano, J.A. & Larrañaga, P. (2001). Performance evaluation of compromise conditional Gaussian networks for data clustering. International Journal of Approximate Reasoning, 28, 23-50.
Peña, J.M., Lozano, J.A., Larrañaga, P. & Inza, I. (2001). Dimensionality reduction in unsupervised learning of conditional Gaussian networks. IEEE Transactions on Pattern Analysis and Machine Intelligence, 23(6), 590–603.
Sierra, B., Serrano, N., Larrañaga, P., Plasencia, E.J., Inza, I., Jiménez, J.J., Revuelta, P. & Mora, M.L. (2001). Using Bayesian networks in the construction of a bi-level multi–classifier. A case study using intensive care unit patients data. Artificial Intelligence in Medicine, 22, 233-248.

Year: 2000

González, C., Lozano, J.A. & Larrañaga, P. (2000). Analyzing the population based incremental learning algorithm by means of discrete dynamical systems. Complex Systems, 12(4), 465–479.
Inza, I., Larrañaga, P., Etxeberria, R. & Sierra, B. (2000). Feature subset selection by Bayesian network–based optimization. Artificial Intelligence, 123, 157-184.
Peña, J.M., Lozano, J.A. & Larrañaga, P. (2000). An improved Bayesian structural EM algorithm for learning Bayesian networks for clustering. Pattern Recognition Letters, 21(8), 779-786.

Year: 1999

Inza, I., Larrañaga, P., Sierra, B., Etxeberria, R., Lozano, J.A. & Peña, J.M. (1999). Representing the behaviour of supervised classification learning algorithms by Bayesian networks. Pattern Recognition Letters, 20(11-13), 1201-1209.
Larrañaga, P., Kuijpers, C.M.H., Murga, R.H., Inza, I. & Dizdarevich, S. (1999). Genetic algorithms for the travelling salesman problem: A review of representations and operators. Artificial Intelligence Review, 13, 129-170.
Lozano, J.A. & Larrañaga, P. (1999). Applying genetic algorithms to search for the best hierarchical clustering of a dataset. Pattern Recognition Letters, 20(9), 911-918.
Lozano, J.A., Larrañaga, P., Graña, M. & Albizuri, F.X. (1999). Genetic algorithms: bridging the convergence gap. Theoretical Computer Science, 229, 11-22.
Peña. J.M., Lozano, J.A. & Larrañaga, P. (1999). An empirical comparison of four initialization methods for the k-means algorithm. Pattern Recognition Letters, 20, 1027-1040.
Peña, J.M., Lozano, J.A. & Larrañaga, P. (1999). Learning Bayesian networks for clustering by means of constructive induction. Pattern Recognition Letters, 20(11-13), 1219-1230.

Year: 1998

Sierra, B. & Larrañaga, P. (1998). Predicting the survival in malignant skin melanoma using Bayesian networks automatically induced by genetic algorithms. An empirical comparison between different approaches. Artificial Intelligence in Medicine, 14(1-2), 215-230.
J. A. Lozano, P. Larrañaga (1998). Aplicación de los algoritmos gen´eticos al problema del clustering jerárquico. Inteligencia Artiﬁcial. Revista Iberoamericana de Inteligencia Artiﬁcial, No. 5, 62-67

Year: 1997

Etxeberria, R., Larrañaga, P. & Pikaza, J.M. (1997). Analysis of the behaviour of genetic algorithms when learning Bayesian network structure from data. Pattern Recognition Letters, 18(11-13), 1269-1273.
Albizuri, X., d’Anjou, A., Graña, M. & Larrañaga, P. (1997). Structure of the high-order Boltzman machine from independence maps. IEEE Transactions on Neural Networks, 8(6), 1351-1358.
Larrañaga, P., Kuijpers, C.M.H., Poza, M. & Murga, R.H. (1997). Decomposing Bayesian networks: triangulation of the moral graph with genetic algorithms. Statistics and Computing, 7(1), 19-34.

Year: 1996

Larrañaga, P., Kuijpers, C.M.H., Murga, R.H. & Yurramendi, Y. (1996). Learning Bayesian network structures by searching for the best ordering with genetic algorithms. IEEE Transactions on System, Man and Cybernetics. Part A: Systems and Humans, 26(4), 487-493.
Larrañaga, P., Poza, M., Yurramendi, Y., Murga, R.H. & Kuijpers, C.M.H. (1996). Structure learning of Bayesian networks by genetic algorithms: A performance analysis of control parameters. IEEE Transactions on Pattern Analysis and Machine Intelligence, 18(9), 912-926.
M. Graña, A. d’Anjou, X. Albizuri, J.A. Lozano, P. Larrañaga, Y. Yurramendi, M. Hernández, J.L. Jiménez, F.J. Torrealdea, M. Poza, A. I. González (1996). Experimentos de aprendizaje con máquinas de Boltzmann de alto orden. Informática y Automática, Vol. 29, No. 4, 42-57
C. M. H. Kuijpers, P. Larrañaga, I. Inza, S. Dizdarevic (1996). Algoritmo genetikoak saltzaile ibiltariaren probleman. Gipuzkoako bira egokiaren atzetik. Elhuyar, Vol. 22, No. 2, 10-30
A. Beristain, J. Castaignéde, J. L. De la Cuesta, I. Dendaluze, I. German, M. González, J. C. Heraut, P. Larrañaga, A. Maeso, E. Vidaurrazaga (1996). La representación social de la delincuencia. Boletín Criminológico. Instituto Andaluz Interuniversitario de Criminología,No. 24, 1-4

Year: 1995

M. González, J. Castaignéde, I. Dendaluce, P. Larrañaga (1995). Representaciones sociales de los jóvenes sobre la criminalidad. Investigación transfronteriza. Revista de Derecho Penal y Criminología, No. 5, 335-490

Year: 1994

P. Larrañaga, J. L. Jiménez, M. Alkorta, J. A. Diego, E. Arnaiz (1994). Aplicación de la clasiﬁcación automática en la construcción de una tipología de residentes. Proyecto Hombre de Gipuzkoa. Eguzkilore, No. 8, 39-51

Year: 1992

P. Echániz, P. Larrañaga, J. Arrizabalaga, J. L. Jiménez, J. A. Iribarren, E. Cuadrado (1992).
Factores

pron´osticos en heroin´omanos infectados por el VIH: an´alisis multivariable de factores serol´ogicos

inespec´ıﬁcos en la evoluci´on de la infecci´on
Factores pronósticos en heroinómanos infectados por el VIH: análisis multivariable de factores serológicosinespecíﬁcos en la evolución de la infección. Revista Clínica Española, 190, (8), 422-426

Year: 1990

A. Beristain, P. Larrañaga, J. L. Jiménez (1990). La policía en la Comunidad Autónoma Vasca. Eguzkilore, No. 4, 189-202
L. Segura, C. Saiz, M. Erquicia, M. T. Gaztañaga, P. Larrañaga, J. L. Jiménez (1990). Estudio comparativo entre tres métodos para la obtención del porcentaje de grasa corporal. Archivos de Medicina del Deporte, Vol. VII, No. 28, 361-364

Year: 1988

Emparanza, J.I., Aldámiz-Echevarria, L., Pérez-Yarza, E.G., Larrañaga, P., Jimenez, J.L., Labiano, M. & Ozcoidi, I. (1988). Prognostic score in acute meningococcemia. Critical Care Medicine, 16(2), 168-169
P. Larrañaga (1988). La indemnización en las víctimas del delito. Un estudio basado en las sentencias dictadas en la audiencia provincial de Guipúzcoa durante el año 1986. Eguzkilore, No. 2, 139-224
P. Angulo, P. Larrañaga (1988). Korden paradoxa. Elhuyar. Zientzia eta Teknika, Vol. 14, 42-43

Year: 1987

J. I. Emparanza, M. Labiano, I. Ozcoidi, P. Larrañaga, L. Aldámiz-Echevarria, E. G. Pérez-Yarza (1987). Score pronóstico para la sepsis meningocócica infantil. Anales Españoles de Pediatría, 346-346
M. Erquicia, P. Larrañaga (1987). Clasiﬁcación de los alimentos utilizando métodos estadísticos. Nutrición Clínica y Dietética Hospitalaria, No. 3/87, 15-22
P. Larrañaga, J. L. Jimenez (1987). Datu-analisia. Elhuyar, Vol. 13, No. 1, 17-24

Year: 1986

P. Larrañaga, J. L. Jimenez (1986). Azpimultzo lausoak. Elhuyar, Vol. 12, No. 2, 45-50

Year: 1985

P. Larrañaga (1985), Datuak sailkatzeko bi metodoen arteko konparaketa. Elhuyar, Vol. 11, No. 3-4, 368-381

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