Biblio

Export 401 results:
2017
Anton-Sanchez, L., P. Larrañaga, R. Benavides-Piccione, I. Fernaud, J. DeFelipe, and C. Bielza, "Three-dimensional spatial modeling of spines along dendritic networks in human cortical pyramidal neurons", PLoS ONE 12(6): e0180400, 2017.
Anton-Sanchez, L., C. Bielza, and P. Larrañaga, "Network Design through Forests with Degree- and Role-constrained Minimum Spanning Trees", Journal of Heuristics, vol. 23, issue 1, pp. 31-51, 2017.
Benjumeda, M., C. Bielza, and P. Larrañaga, "Tractability of Most Probable Explanations in Multidimensional Bayesian Network Classifiers", International Journal of Approximate Reasoning, to appear, 2017.
Díaz-Rozo, J., C. Bielza, and P.. Larrañaga, "Machine Learning-based CPS for Clustering High throughput Machining Cycle Conditions", Procedia Manufacturing Elsevier (no JCR), vol. 10, pp. 997-1008, 2017.
Fernandez-Gonzalez, P., C. Bielza, and P. Larrañaga, "Univariate and bivariate truncated von Mises distributions", Progress in Artificial Intelligence (no JCR), pp. 1-10, 2017.
Fernandez-Gonzalez, P., R. Benavides-Piccione, I. Leguey, C. Bielza, P. Larrañaga, and J. DeFelipe, "Dendritic branching angles of pyramidal neurons of the human cerebral cortex", Brain Structure and Function, vol. 222, issue 4, pp. 1847-1859, 2017.
Mu, J., K. R. Chaudhuri, C. Bielza, D. Pedro J., P. Larrañaga, and P. Martínez-Martín, "Parkinson's Disease Subtypes Identified from Cluster Analysis of Motor and Non-motor Symptoms", Frontiers in Aging Neuroscience, vol. 9, 20/09/2017.
Ogbechie, A., J. Díaz-Rozo, P. Larrañaga, and C. Bielza, "Dynamic Bayesian Network-Based Anomaly Detection for In-Process Visual Inspection of Laser Surface Heat Treatment", Machine Learning for Cyber Physical Systems: Selected papers from the International Conference ML4CPS 2016: Springer Berlin Heidelberg, pp. 17-24, 2017.
Rodriguez-Lujan, L., P. Larrañaga, and C. Bielza, "Frobenius norm regularization for the multivariate von Mises distribution", International Journal of Intelligent Systems, vol. 32, issue 2, pp. 153–176, 2017.
2016
Anton-Sanchez, L., C. Bielza, P. Larrañaga, and J. DeFelipe, "Wiring Economy of Pyramidal Cells in the Juvenile Rat Somatosensory Cortex", PLoS ONE, vol. 11, issue 11, 2016.
Anton-Sanchez, L., C. Bielza, R. Benavides-Piccione, J. DeFelipe, and P. Larrañaga, "Dendritic and axonal wiring optimization of cortical GABAergic interneurons", Neuroinformatics, vol. 14, issue 4, pp. 453-464, 2016.
Atienza, D., C. Bielza, and P. Larrañaga, "Anomaly Detection with a Spatio-Temporal Tracking of the Laser Spot", Proceedings of the Eight European Starting AI Researcher Symposium (STAIRS 2016), pp. 137-142, 2016.
Benjumeda, M., C. Bielza, and P. Larrañaga, "Learning tractable multidimensional Bayesian network classifiers", Proceedings of the Eighth International Conference on Probabilistic Graphical Models, vol. 52, pp. 13-24, 2016.
Benjumeda, M., C. Bielza, and P. Larrañaga, "Learning Bayesian networks with low inference complexity", Progress in Artificial Intelligence (no JCR), vol. 5, issue 1, pp. 15-26, 2016.
Borchani, H., P. Larrañaga, J. Gama, and C. Bielza, "Mining multi-dimensional concept-drifting data streams using Bayesian network classifiers", Intelligent Data Analysis, vol. 20, no. 2, 2016.
Córdoba-Sánchez, I., and J. de Lara, "Ann: A domain-specific language for the effective design and validation of Java annotations", Computer Languages, Systems and Structures, vol. 45, pp. 164-190, 2016.
Córdoba-Sánchez, I., C. Bielza, and P. Larrañaga, Graphoids and separoids in model theory, , no. TR:UPM-ETSIINF/DIA/2016-1: Universidad Politécnica de Madrid, 2016.
Diaz, J., C. Bielza, J.L. Ocaña, and P. Larra˜naga, "Development of a Cyber-Physical System based on selective Gaussian naïve Bayes model for a self-predict laser surface heat treatment process control", Machine Learning for Cyber Physical Systems: Selected papers from the International Conference ML4CPS 2015: Springer Berlin Heidelberg, pp. 1-8, 2016.
Diaz, J., C. Bielza, J.L. Ocaña, and P. Larrañaga, "Development of a Cyber-Physical System based on selective Gaussian naïve Bayes model for a self-predict laser surface heat treatment process control", Machine Learning for Cyber Physical Systems: Selected papers from the International Conference ML4CPS 2015: Springer Berlin Heidelberg, pp. 1-8, 2016.
Fernandez-Gonzalez, P., P. Larrañaga, and C. Bielza, "Bayesian Gaussian networks for multidimensional classifi cation of morphologically characterized neurons in the NeuroMorpho repository", CAEPIA, 17th, 2016.
Larrañaga, P., "Bayesian networks for neuroscience", Workshop on Advances and Applications on Data Science and Engineering, Madrid, Real Academia de Ingenieria, 2016.
Leguey, I., C. Bielza, P. Larrañaga, A. Kastanauskaite, C. Rojo, R. Benavides-Piccione, and J. DeFelipe, "Dendritic branching angles of pyramidal cells across layers of the juvenile rat somatosensory cortex", Journal of Comparative Neurology, vol. 524, issue 13, pp. 2567-2576, 2016.
Leguey, I., C. Bielza, and P. Larrañaga, "Tree-structured Bayesian networks for wrapped Cauchy directional distributions", CAEPIA, Salamanca, Springer, pp. 207-216, 2016.
Leitner, L., C. Bielza, S. L. Hill, and P. Larrañaga, "Data Publications Correlate with Citation Impact", Frontiers in Neuroscience, vol. 10, issue 419, 2016.
Luengo-Sanchez, S., C. Bielza, and P. Larrañaga, "Hybrid Gaussian and von Mises model-based clustering", European Conference on Artificial Intelligence, vol. 285, pp. 855-862, 2016.
Ogbechie, A., J. Díaz-Rozo, P. Larrañaga, and C. Bielza, "Dynamic Bayesian Network-Based Anomaly Detection for In-Process Visual Inspection of Laser Surface Heat Treatment", ML4CPS - Machine Learning for Cyber ​​Physical Systems and Industry 4.0, Karlsruhe, Germany, Springer, 2016.
Rojo, C., I. Leguey, A. Kastanauskaite, C. Bielza, P.. Larrañaga, J.. DeFelipe, and R.. Benavides-Piccione, "Laminar differences in dendritic structure of pyramidal neurons in juvenile rat somatosensory cortex", Cerebral Cortex, vol. 26, issue 6, pp. 2811-2822, 2016.
Varando, G., C. Bielza, and P. Larrañaga, "Decision Functions for Chain Classifiers based on Bayesian Networks for Multi-Label Classification", International Journal of Approximate Reasoning, vol. 68, pp. 164-178, 2016.
2015
Anton-Sanchez, L., Computación evolutiva de bosques de expansión mínimos con restricción de grado y de rol, , (supervised by C. Bielza and P. Larrañaga), Departamento de Inteligencia Artificial, Universidad Politécnica de Madrid, 2015.
Anton-Sanchez, L., C. Bielza, and P. Larrañaga, Evolutionary computation of forests with Degree- and Role-Constrained Minimum Spanning Trees, : UPM, 2015.
Benjumeda, M., P. Larrañaga, and C. Bielza, "Learning low inference complexity Bayesian networks", Proc. of the Conference of the Spanish Association for Artificial Intelligence (CAEPIA), 2015.
Bielza, C., J. Gama, A. Jorge, and I. Žliobaité, "Guest Editors introduction: special issue of the ECMLPKDD 2015 journal track", Machine Learning, vol. 100, pp. 157–159, 2015.
Bielza, C., S. Moral, and A. Salmerón, "Recent advances in probabilistic graphical models", International Journal of Intelligent Systems, vol. 30, pp. 207-208, 2015.
Bielza, C., J. Gama, A. Jorge, and I. Žliobaité, "Guest Editors introduction: special issue of the ECMLPKDD 2015 journal track", Data Mining and Knowledge Discovery, vol. 29, pp. 1113–1115, 2015.
Borchani, H., G. Varando, C. Bielza, and P. Larrañaga, "A survey on multi-output regression", WIREs Data Mining and Knowledge Discovery, vol. 5, pp. 216--233, 2015.
Córdoba-Sánchez, I., C. Bielza, and P. Larrañaga, "Towards Gaussian Bayesian Network Fusion", Symbolic and Quantitative Approaches to Reasoning with Uncertainty, LNAI 9161, vol. 9161: Springer International Publishing, pp. 519-528, July, 2015.
Córdoba-Sánchez, I., Fusión de redes Bayesianas Gaussianas, , (supervised by C. Bielza and P. Larrañaga), Departamento de Inteligencia Artificial, Universidad Politécnica de Madrid, 2015.
Córdoba-Sánchez, I., and J. Lara, "A modelling language for the effective design of Java annotations", Proceedings of the 30th Annual ACM Symposium on Applied Computing (SAC '15), New York, NY, USA, ACM, pp. 2087-2092, April, 2015.
Diaz-Rozo, J., J. Posada, I. Barandiaran, and C. Toro, "Recommendations for sustainability in production from a machine-tool manufacturer", KES-SDM, 2015.
Diaz-Rozo, J., C. Bielza, J. Luis Ocaña, and P. Larrañaga, "Machine Learning for Cyber Physical Systems ML4CPS", Development of a Cyber-Physical System based on selective Gaussian naive Bayes model for a self-predict laser surface heat treatment process control: Springer Vieweg, 2015.
Fernández-González, P., C. Bielza, and P. Larrañaga, Univariate and bivariate truncated von Mises distributions, TR:UPM-ETSINF/DIA/2015-1, : Universidad Politécnica de Madrid, January, 2015.
Fernandez-Gonzalez, P., C. Bielza, and P. Larrañaga, "Multidimensional classifiers for neuroanatomical data", ICML Workshop on Statistics, Machine Learning and Neuroscience (Stamlins 2015), Lille, France, ICML, Jul 2015.
Ibañez, A., R. Armañanzas, C. Bielza, and P. Larrañaga, "Genetic algorithms and Gaussian Bayesian networks to uncover the predictive core set of bibliometric indices", Journal of the American Society for Information Science and Technology, vol. 67, issue 7, pp. 1703–1721, 2015.
Ibáñez, A., Machine Learning in Scientometrics, , (supervised by C. Bielza and P. Larrañaga), Departamento de Inteligencia Artificial, Universidad Politécnica de Madrid, 2015.
Karshenas, H., C. Bielza, and P. Larrañaga, "Interval-based ranking in noisy evolutionary multi-objective optimization", Computational Optimization and Applications, vol. 61, issue 2, pp. 517-555, 2015.
Krallinger, M., O. Rabal, F. Leitner, and et. al., "The CHEMDNER corpus of chemicals and drugs and its annotation principles", Journal of Chemoinformatics, vol. 7, no. Suppl 1, pp. S2, 2015.
Krallinger, M., F. Leitner, and O. Rabal, "CHEMDNER: The drugs and chemical names extraction challenge", Journal of Chemoinformatics, vol. T, no. Suppl 1, pp. S1, 2015.
Larrañaga, A., C. Bielza, P. Pongrácz, T. Faragó, P. Bálint, and P. Larrañaga, "Comparing supervised learning methods for classifying sex, age, context and individual Mudi dogs from barking", Animal Cognition, vol. 18, no. 2, pp. 405-421, 2015.
Lopez-Cruz, P. L., C. Bielza, and P. Larrañaga, "Directional naive Bayes classifiers", Pattern Analysis and Applications, vol. 18, pp. 225-246, 2015.
Luengo-Sanchez, S., C. Bielza, R. Benavides-Piccione, I. Fernaud-Espinosa, J. DeFelipe, and P. Larrañaga, "A univocal definition of the neuronal soma morphology using Gaussian mixture models", Frontiers in Neuroanatomy, vol. 9, issue 137, 2015.
Masegosa, A., R. Armañanzas, M. A. Grau, V. Potenciano, S. Moral, P. Larrañaga, C. Bielza, and F. Matesanz, "Discretization of Expression Quantitative Trait Loci in Association Analysis Between Genotypes and Expression Data", Current Bioinformatics, vol. 10, no. 2, pp. 144-164, 2015.
Mihaljevic, B., R. Benavides-Piccione, L. Guerra, J. DeFelipe, P. Larrañaga, and C. Bielza, "Classifying GABAergic interneurons with semi-supervised projected model-based clustering", Artificial Intelligence in Medicine, vol. 65, issue 1, pp. 49-59, 2015.
Mihaljevic, B., R. Benavides-Piccione, C. Bielza, J. DeFelipe, and P. Larrañaga, "Bayesian network classifiers for categorizing cortical GABAergic interneurons", Neuroinformatics, vol. 13, no. 2, pp. 192–208, April, 2015.
Ochoa, A., J. Diaz-Rozo, and B. Kamp, "Insights for Industry 4.0 Implementation in machine tool servitization", International Virtual Concept Workshop on INDUSTRIE 4.0, 2015.
Ochoa, A., J. Diaz-Rozo, and B. Kamp, "Challenges and opportunities for servitization in the machine tool industry in the era of Industry 4.0", 4th International Conference on Business Servitization, 2015.
Olazarán, J., M. Valentí, B. Frades, M. Ascensión Zea-Sevilla, M. Ávila-Villanueva, M. Ángel Fernández-Blázquez, M. Calero, J. Luis Dobato, J. Antonio Hernández-Tamames, B. León-Salas, L. Agüera-Ortiz, J. López-Álvarez, P. Larrañaga, C. Bielza, J. Álvarez-Linera, and P. Martínez-Martín, "The Vallecas Project: a cohort to identify early markers and mechanisms of Alzheimer’s disease", Frontiers in Aging Neuroscience, vol. 7, pp. 181, 2015.
Rodriguez-Lujan, L., C. Bielza, and P. Larrañaga, "Regularized Multivariate von Mises Distribution", Proc. of the Conference of the Spanish Association for Artificial Intelligence (CAEPIA), 2015.
Varando, G., P. L. Lopez-Cruz, T. D. Nielsen, P. Larrañaga, and C. Bielza, "Conditional density approximations with mixtures of polynomials", International Journal of Intelligent Systems, vol. 30, no. 3, pp. 236–264, 2015.
Varando, G., C. Bielza, and P. Larrañaga, "Decision Boundary for Discrete Bayesian Network Classifiers", Journal of Machine Learning Research, vol. 16, pp. 2725-2749, 2015.
2014
Anton-Sanchez, L., C. Bielza, A. Merchán-Pérez, J. R. Rodríguez, J. DeFelipe, and P. Larrañaga, "Three-dimensional distribution of cortical synapses: a replicated point pattern-based analysis", Frontiers in Neuroanatomy, vol. 8, pp. Article 85, 2014, Also available in the ebook: http://www.frontiersin.org/books/Quantitative_Analysis_of_Neuroanatomy/829.
Benjumeda, M., Learning Bayesian Networks From Data by the Incremental Compilation of Polynomial Trees, , (supervised by C. Bielza and P. Larrañaga), Departamento de Inteligencia Artificial, Universidad Politécnica de Madrid, 2014.
Bielza, C., and P. Larrañaga, "Bayesian networks in neuroscience: A survey", Frontiers in Computational Neuroscience, vol. 8, pp. Article 131, 2014.
Bielza, C., R. Benavides-Piccione, P. L. Lopez-Cruz, P. Larrañaga, and J. DeFelipe, "Branching angles of pyramidal cell dendrites follow common geometrical design principles in different cortical areas", Scientific Reports, vol. 4, pp. Article 5909, 2014.
Bielza, C., and P. Larrañaga, "Discrete Bayesian Network Classifiers: A Survey", ACM Computing Surveys, vol. 47, no. 1, pp. Article 5, 2014.
Borchani, H., C. Bielza, P. Martínez-Martín, and P. Larrañaga, "Predicting EQ-5D from the Parkinson’s disease questionnaire PDQ-8 using multi-dimensional Bayesian network classifiers", Biomedical Engineering: Applications, Basis and Communications, vol. 26, no. 1, pp. 1450015, 2014.
Fernandez-Gonzalez, P., Contributions to the truncated von Mises Distribution for the Univariate and Bivariate case, , (supervised by C. Bielza and P. Larrañaga), Departamento de Inteligencia Artificial, Universidad Politécnica de Madrid, 2014.
Guerra, L., C. Bielza, V. Robles, and P. Larrañaga, "Semi-supervised projected model-based clustering", Data Mining and Knowledge Discovery, vol. 28, no. 4, pp. 882-917, 2014.
Ibañez, A., C. Bielza, and P. Larrañaga, "Cost-sensitive selective naive Bayes classifiers for predicting the increase of the h-index for scientific journals", Neurocomputing, vol. 135, no. 5, pp. 45-52, 2014.
Karshenas, H., R. Santana, C. Bielza, and P. Larrañaga, "Multi-objective estimation of distribution algorithm based on joint modeling of objectives and variables", IEEE Transactions on Evolutionary Computation, vol. 18, no. 4, pp. 519-542, 2014.
Lopez-Cruz, P. L., C. Bielza, and P. Larrañaga, "Learning mixtures of polynomials of multidimensional probability densities from data using B-spline interpolation", International Journal of Approximate Reasoning, vol. 55, no. 4, pp. 989–1010, 2014.
Lopez-Cruz, P. L., P. Larrañaga, , and C. Bielza, "Bayesian network modeling of the consensus between experts: An application to neuron classification", International Journal of Approximate Reasoning, vol. 55, no. 1, pp. 3-22, 2014.
Luengo-Sanchez, S., Clustering basado en redes bayesianas con predictoras continuas: aplicaciones en neurociencia, , (supervised by C. Bielza and P. Larrañaga), Departamento de Inteligencia Artificial, Universidad Politécnica de Madrid, 2014.
Merchán-Pérez, A., R. Rodríguez, S. González, V. Robles, J. DeFelipe, P. Larrañaga, and C. Bielza, "Three-dimensional spatial distribution of synapses in the neocortex: A dual-beam electron microscopy study", Cerebral Cortex, vol. 24, pp. 1579-1588, 2014.
Mihaljevic, B., C. Bielza, R. Benavides-Piccione, J. DeFelipe, and P. Larrañaga, "Multi-dimensional classification of GABAergic interneurons with Bayesian network-modeled label uncertainty", Frontiers in Computional Neuroscience, vol. 8, pp. Article 150, 2014.
Morales, J., R. Benavides-Piccione, M. Dar, I. Fernaud, A. Rodríguez, L. Anton-Sanchez, C. Bielza, P. Larrañaga, J. DeFelipe, and R. Yuste, "Random positions of dendritic spines in human cerebral cortex", Journal of Neuroscience, vol. 34, no. 30, pp. 10078-10084, 2014.
Read, J., C. Bielza, and P. Larrañaga, "Multi-dimensional classification with super-classes", IEEE Transactions on Knowledge and Data Engineering, vol. 26, no. 7, pp. 1720-1733, 2014.
Sucar, E., C. Bielza, E. F. Morales, P. Hernandez-Leal, J. H. Zaragoza, and P. Larrañaga, "Multi-label Classification with Bayesian Network-based Chain Classifiers", Pattern Recognition Letters, vol. 41, pp. 14-22, 2014.
Varando, G., C. Bielza, and P. Larrañaga, Decision boundary for discrete Bayesian network classifiers, TR:UPM-ETSIINF/DIA/2014-1, : UPM, 2014.
Varando, G., C. Bielza, and P. Larrañaga, "Expressive Power of Binary Relevance and Chain Classifiers Based on Bayesian Networks for Multi-Label Classification", Lecture Notes in Artificial Intelligence, 8754: Springer, pp. 519-534, 2014.
2013
Anton-Sanchez, L., C. Bielza, and P. Larrañaga, "Towards optimal neuronal wiring through estimation of distribution algorithms", Proceedings of the 15h Annual Conference companion on Genetic and Evolutionary Computation Conference Companion, New York, NY, USA, ACM, pp. 1647-1650, 2013.
Armañanzas, R., L. Alonso-Nanclares, J. DeFelipe, A. Kastanauskaite, R. G. de Sola, J. DeFelipe, C. Bielza, and P. Larrañaga, "Machine learning approach for the outcome prediction of temporal lobe epilepsy surgery", PLoS ONE, vol. 8, no. 4, pp. e62819, 2013.
Armañanzas, R., C. Bielza, K. R. Chaudhuri, P. Martínez-Martín, and P. Larrañaga, "Unveiling relevant non-motor Parkinson's disease severity symptoms using a machine learning approach", Artificial Intelligence in Medicine, vol. 58, no. 3, pp. 195-202, 2013.
Bielza, C., A. Salmerón, A. Alonso-Betanzos, J. I. Hidalgo, L. Martínez, A. Troncoso, E. Corchado, and J. M. Corchado, "Advances in Artificial Intelligence, Lecture Notes in Artificial Intelligence (8109)", Lecture Notes in Artificial Intelligence, vol. 8109: Springer, 2013.
Bielza, C., J. A. Fernandez del Pozo, and P. Larrañaga, "Parameter control of genetic algorithms by learning and simulation of Bayesian Networks. A case study for the optimal ordering of tables", Journal of Computer Science and Technology, vol. 28, no. 4, pp. 720-731, 2013.
Borchani, H., Multi-dimensional classification using Bayesian networks for stationary and evolving streaming data, , (supervised by C. Bielza and P. Larrañaga), Departamento de Inteligencia Artificial, Universidad Politécnica de Madrid, 2013.
Borchani, H., C. Bielza, , and P. Larrañaga, "Predicting human immunodeficiency virus inhibitors using multi-dimensional Bayesian network classifiers", Artificial Intelligence in Medicine, vol. 57, no. 3, pp. 219-229, 2013.
DeFelipe, J., P. L. Lopez-Cruz, R. Benavides-Piccione, C. Bielza, P. Larrañaga, and et. al., "New insights into the classification and nomenclature of cortical GABAergic interneurons", Nature Reviews Neuroscience, vol. 14, no. 3, pp. 202-216, 2013.
Flores, J. L., I. Inza, P. Larrañaga, and B. Calvo, "A new measure for gene expression biclustering based on non-parametric correlation", Computer Methods and Programs in Biomedicine, vol. 113, no. 3, pp. 367-397, 2013.
García-Escudero, R., J. M. Paramio, P. Larrañaga, and C. Bielza, Test Predictor de Supervivencia Global de Adenocarcinoma de Pulmón, , Granting date: 26-4-2013, 2013.
García-Torres, M., R. Armañanzas, C. Bielza, and P. Larrañaga, "Comparison of metaheuristic strategies for peakbin selection in proteomic mass spectrometry data", Information Sciences, vol. 222, pp. 229-246, 2013.
Guerra, L., R. Benavides-Piccione, C. Bielza, V. Robles, J. DeFelipe, and P. Larrañaga, "Semi-supervised projected clustering for classifying GABAergic interneurons", Artificial Intelligence in Medicine 2013, LNAI 7885: Springer, pp. 156–165, 2013.
Ibañez, A., C. Bielza, and P. Larrañaga, "Análisis de la actividad científica de las universidades públicas españolas en el área de las tecnologías informáticas", Revista Española de Documentación Científica, vol. 36, no. 1, pp. e002, 2013.
Ibañez, A., C. Bielza, and P. Larrañaga, "Relationship among research collaboration, number of documents and number of citations. A case study in Spanish computer science production in 2000-2009", Scientometrics, vol. 95, no. 2, pp. 689-716, 2013.
Ibañez, A., P. Larrañaga, and C. Bielza, "Cluster methods for assessing research performance: exploring Spanish computer science", Scientometrics, vol. 97, pp. 571-600, 2013.
Karshenas, H., R. Santana, C. Bielza, and P. Larrañaga, "Regularized continuous estimation of distribution algorithms", Applied Soft Computing, vol. 13, no. 5, pp. 2412–2432, 2013.
Karshenas, H., Regularized Model Learning in EDAs for Continuous and Multi-Objective Optimization, , (supervised by C. Bielza and P. Larrañaga), Departamento de Inteligencia Artificial, Universidad Politécnica de Madrid, 2013.
Larrañaga, P., H. Karshenas, C. Bielza, and R. Santana, "A review on evolutionary algorithms in Bayesian network learning and inference tasks", Information Sciences, vol. 233, pp. 109-125, 2013.
Lopez-Cruz, P. L., T. D. Nielsen, C. Bielza, and P. Larrañaga, "Learning mixtures of polynomials of conditional densities from data", Advances in Artificial Intelligence, Proceedings of the 15th MultiConference of the Spanish Association for Artificial Intelligence, LNCS 8109: Springer, pp. 363-372, 2013.
Lopez-Cruz, P. L., Contributions to Bayesian network learning with applications to neuroscience, , (supervised by C. Bielza and P. Larrañaga), Departamento de Inteligencia Artificial, Universidad Politécnica de Madrid, 2013.
Lopez-Cruz, P. L., C. Bielza, and P. Larrañaga, "Learning conditional linear Gaussian classifiers with probabilistic class labels", Advances in Artificial Intelligence, Proceedings of the 15th MultiConference of the Spanish Association for Artificial Intelligence, LNCS 8109: Springer, pp. 139-148, 2013.
Mihaljevic, B., P. Larrañaga, and C. Bielza, "Augmented Semi-naive Bayes Classifier", Advances in Artificial Intelligence, Proceedings of the 15th MultiConference of the Spanish Association for Artificial Intelligence, LNAI 8109: Springer, pp. 159-167, 2013.
Mihaljevic, B., BayesClass. An R package for learning Bayesian network classifiers. Applications to neuroscience, , (supervised by C. Bielza and P. Larrañaga), Departamento de Inteligencia Artificial, Universidad Politécnica de Madrid, 2013.
Morales, D., Y. Vives-Gilabert, B. Gómez-Ansón, E. Bengoetxea, P. Larrañaga, C. Bielza, J. Pagonabarraga, J. Kulisevsky, I. Corcuera-Solano, and M. Delfino, "Predicting dementia development in Parkinson's disease using Bayesian network classifiers", Psychiatry Research: NeuroImaging, vol. 213, pp. 92-98, 2013.
Santana, R., L. McGarry, C. Bielza, P. Larrañaga, and R. Yuste, "Classification of neocortical interneurons using affinity propagation", Frontiers in Neural Circuits, vol. 7:185, 2013.
Santana, R., R. Armañanzas, C. Bielza, and P. Larrañaga, "Network measures for information extraction in evolutionary algorithms", International Journal of Computational Intelligence Systems, vol. 6, no. 6, pp. 1163-1188, 2013.
Santana, R., C. Bielza, and P. Larrañaga, Changing conduction delays to maximize the number of polychronous groups with an estimation of distribution algorithm, , Technical Report, UPM-FI/DIA/2013-1, Technical University of Madrid, 2013.
Vidaurre, D., C. Bielza, and P. Larrañaga, "Sparse regularized local regression", Computational Statistics and Data Analysis, vol. 62, pp. 122-135, 2013.
Vidaurre, D., C. Bielza, and P. Larrañaga, "Classification of neural signals from sparse autoregressive features", Neurocomputing, vol. 111, pp. 21-26, 2013.
Vidaurre, D., C. Bielza, and P. Larrañaga, "An L1-regularized naive Bayes-inspired classifier for discarding redundant and irrelevant predictors", International Journal on Artificial Intelligence Tools, vol. 22, no. 4, pp. 1350019, 2013.
Vidaurre, D., M. van Gerven, C. Bielza, P. Larrañaga, and T. Heskes, "Bayesian sparse partial least squares", Neural Computation, vol. 25, no. 12, pp. 3318–3339, 2013.
Vidaurre, D., C. Bielza, and P. Larrañaga, "A survey on L1-regression", International Statistical Review, vol. 81, no. 3, pp. 361-387, 2013.
2012
Armañanzas, R., P. Larrañaga, and C. Bielza, "Ensemble transcript interaction networks: A case study on Alzheimer's disease", Computer Methods and Programs in Biomedicine, vol. 108, no. 1, pp. 442-450, 2012.
Armañanzas, R., P. Martínez-Martín, C. Bielza, and P. Larrañaga, "Restating clinical impression of severity index for Parkinson's disease using just non-motor criteria", Proceedings of the 25th European Conference on Operational Research, Vilnius, Lithuania, pp. 231-232, 2012.
Borchani, H., C. Bielza, P. Martínez-Martín, and P. Larrañaga, "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, vol. 45, pp. 1175-1184, 2012.
Calvo, B., I. Inza, P. Larrañaga, and J. A. Lozano, "Wrapper positive Bayesian network classifiers", Knowledge and Information Systems, vol. 33, no. 3, pp. 631-654, 2012.
Dueñas, M., M. Santos, F. J. F. J Aranda, C. Bielza, A. B. Martínez-Cruz, C. Lorz, M. Taron, E. M. Ciruelos, J. L. Rodríguez-Peralto, M. Martín, P. Larrañaga, J. Dahabreh, G. P. Stathopoulos, R. Rosell, J. M. Paramio, and R. García-Escudero, "Mouse p53-deficient cancer models as platforms for obtaining genomic predictors of human cancer clinical outcomes", PLoS One, vol. 7, no. 8, pp. e42494, 2012.
García-Bilbao, A., R. Armañanzas, Z. Ispizua, B. Calvo, A. Alonso-Varona, I. Inza, P. Larrañaga, G. López Vivanco, B. Suárez-Merino, and M. Betanzos, "Identification of a biomarker panel for colorectal cancer diagnosis", Proceedings of the 6th International Meeting on Biotechnology, Bilbao, Spain, pp. 77, 2012.
García-Bilbao, A., R. Armañanzas, Z. Ispizua, B. Calvo, A. Alonso-Varona, I. Inza, P. Larrañaga, G. López-Vivanco, B. Suárez-Merino, and M. Betanzos, "Identification of a biomarker panel for colorectal cancer diagnosis", BMC Cancer, vol. 12, no. 43, 2012.
Guerra, L., V. Robles, C. Bielza, and P. Larrañaga, "A comparison of clustering quality indices using outliers and noise", Intelligent Data Analysis, vol. 16, no. 4, pp. 703-715, 2012.
Guerra, L., Semi-supervised subspace clustering and applications to neuroscience, , (supervised by C. Bielza and V. Robles), Departamento de Inteligencia Artificial, Universidad Politécnica de Madrid, 2012.
Karshenas, H., R. Santana, C. Bielza, and P. Larrañaga, "Continuous Estimation of Distribution Algorithms Based on Factorized Gaussian Markov Networks", Markov Networks in Evolutionary Algorithms: Springer, pp. 157-173, 2012.
Karshenas, H., P. Larrañaga, Q. Zhang, and C. Bielza, An interval-based multi-objective approach to feature subset selection using joint modeling of objectives and variables, , Technical Report, UPM-FI/DIA/2012-1, Technical University of Madrid, 2012.
Karshenas, H., R. Santana, C. Bielza, and P. Larrañaga, Multi-objective Estimation of Distribution Algorithm based on joint modelling of objectives and variables, , Technical Report, UPM-FI/DIA/2012-2, Technical University of Madrid, 2012.
Larrañaga, P., H. Karshenas, C. Bielza, and R. Santana, "A review on probabilistic graphical models in evolutionary computation", Journal of Heuristics, vol. 18, no. 5, pp. 795-819, 2012.
Lopez-Cruz, P. L., C. Bielza, and P. Larrañaga, "Learning mixtures of polynomials from data using B-spline interpolation", Sixth European Workshop on Probabilistic Graphical Models (PGM 2012), Granada, Spain, pp. 271-278, 2012.
Maojo, V., M. Garcia-Remesal, C. Bielza, J. Crespo, D. Perez-Rey, and C. Kulikowski, "Biomedical Informatics Publications: A Global Perspective. Part I: Conferences", Methods of Information in Medicine, vol. 51, no. 1, pp. 82-90, 2012.
Maojo, V., M. Garcia-Remesal, C. Bielza, J. Crespo, D. Perez-Rey, and C. Kulikowski, "Biomedical Informatics Publications: A Global Perspective. Part II: Journals", Methods of Information in Medicine, vol. 51, no. 2, pp. 131-137, 2012.
Santana, R., C. Bielza, and P. Larrañaga, "Conductance interaction identification by means of Boltzmann distribution and mutual information analysis in conductance-based neuron models", BMC Neuroscience, vol. 13, no. Suppl 1, pp. P100, 2012.
Santana, R., C. Bielza, and P. Larrañaga, "Regularized logistic regression and multi-objective variable selection for classifying MEG data", Biological Cybernetics, vol. 106, no. 6-7, pp. 389-405, 2012.
Santana, R., C. Bielza, and P. Larrañaga, "Maximizing the number of polychronous groups in spiking networks", Companion Material Proceedings of the 14th Annual Genetic and Evolutionary Computation Conference (GECCO-2012): ACM Digital Library, pp. 1499-1500, 2012.
Vidaurre, D., C. Bielza, and P. Larrañaga, "Lazy lasso for local regression", Computational Statistics, vol. 27, no. 3, pp. 531-550, 2012.
Vidaurre, D., Regularization for sparsity in statistical analysis and machine learning, , (supervised by Pedro Larrañaga and Concha Bielza), Departamento de Inteligencia Artificial, Universidad Politécnica de Madrid, 2012.
Vidaurre, D., E. E. Rodríguez, C. Bielza, P. Larrañaga, and P. Rudomin, "A new feature extraction method for signal classification applied to cat spinal cord signals", Journal of Neural Engineering, vol. in press, 2012.
2011
Armañanzas, R., C. Bielza, P. Larrañaga, and P. Martínez-Martín, Restating Parkinson's disease severity indices by means of non-motor criteria, , Technical Report, UPM-FI/DIA/2011-2, 2011.
Armañanzas, R., Y. Saeys, I. Inza, M. Garca-Torres, C. Bielza, Y. van de Peer, and P. Larrañaga, "Peakbin selection in mass spectrometry data using a consensus approach with estimation of distribution algorithms", IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 8, no. 3, pp. 760-774, 2011.
Bengoetxea, E., P. Larrañaga, C. Bielza, and J. A. Fernandez del Pozo, "Optimal Row and Column Ordering to Improve Table Interpretation Using Estimation of Distribution Algorithms", Journal of Heuristics, vol. 17, no. 5, pp. 567-588, 2011.
Bielza, C., M. Gómez, and P. Shenoy, "A Review of Representation Issues and Modelling Challenges with Influence Diagrams", Omega -The International Journal of Management Science, vol. 39, pp. 227-241, 2011.
Bielza, C., V. Robles, and P. Larrañaga, "Regularized Logistic Regression without a Penalty Term: An Application to Cancer Classification with Microarray Data", Expert Systems with Applications, vol. 38, pp. 5110-5118, 2011.
Bielza, C., G. Li, and P. Larrañaga, "Multi-Dimensional Classification with Bayesian Networks", International Journal of Approximate Reasoning, vol. 52, pp. 705-727, 2011.
Borchani, H., C. Bielza, and P. Larrañaga, "Learning multi-dimensional Bayesian network classifiers using Markov blankets: A case study in the prediction of HIV protease inhibitors", AIME'11 Workshop on Probabilistic Problem Solving in Biomedicine, 2011.
Borchani, H., P. Larrañaga, and C. Bielza, "Classifying evolving data streams with partially labeled data", Intelligent Data Analysis, vol. 15, no. 5, pp. 655-670, 2011.
Fernandez del Pozo, J. A., and C. Bielza, "Dealing with Complex Queries in Decision Support Systems", Data {&} Knowledge Engineering, vol. 70, pp. 167-181, 2011.
Guerra, L., L. McGarry, V. Robles, C. Bielza, P. Larrañaga, and R. Yuste, "Comparison between Supervised and Unsupervised Classification of Neuronal Cell Types: A Case Study", Developmental Neurobiology, vol. 71, no. 1, pp. 71-82, 2011.
Ibañez, A., P. Larrañaga, and C. Bielza, "Predicting the h-index with cost-sensitive naive Bayes", 11th International Conference on Intelligent Systems Design and Applications: IEEE SMC, pp. 599-604, 2011.
Ibañez, A., P. Larrañaga, and C. Bielza, "Using Bayesian networks to discover relationships between bibliometric indices. A case study of computer science and artificial intelligence journals", Scientometrics, vol. 89, no. 2, pp. 523-551, 2011.
Ibañez, A., C. Bielza, and P. Larrañaga, Productividad y visibilidad científica de los profesores funcionarios de las universidades públicas españolas en el área de tecnologías informáticas, : Fundación General de la UPM, 2011.
Karshenas, H., R. Santana, C. Bielza, and P. Larrañaga, Regularized Model Learning in Estimation of Distribution Algorithms for Continuous Optimization Problems, , Technical Report, UPM-FI/DIA/2011-1, Technical University of Madrid, 2011.
Karshenas, H., R. Santana, C. Bielza, and P. Larrañaga, "Multi-Objective Optimization with Joint Probabilistic Modeling of Objectives and Variables", Lecture Notes in Computer Science, no. 6576: Springer, pp. 298-312, 2011.
Larrañaga, P., and S. Moral, "Probabilistic graphical models in artificial intelligence", Applied Soft Computing, vol. 11, no. 2, pp. 1511-1528, 2011.
Lopez-Cruz, P. L., C. Bielza, P. Larrañaga, R. Benavides-Piccione, and J. DeFelipe, "Models and simulation of 3D neuronal dendritic trees using Bayesian networks", Neuroinformatics, vol. 9, no. 4, pp. 347-369, 2011.
Lopez-Cruz, P. L., C. Bielza, and P. Larrañaga, "The von Mises naive Bayes classifier for directional data", Advances in Artificial Intelligence, 14th Conference of the Spanish Association for Artificial Intelligence, vol. 7023: Springer, pp. 145-154, 2011.
Santana, R., C. Bielza, and P. Larrañaga, "Affinity Propagation Enhanced by Estimation of Distribution Algorithms", Proceedings of the 2011 Genetic and Evolutionary Conference (GECCO-2011): ACM Digital Library, pp. 331–338, 2011.
Santana, R., C. Bielza, and P. Larrañaga, "Optimizing brain networks topologies using multi-objective evolutionary computation", Neuroinformatics, vol. 9, no. 1, pp. 3-19, 2011.
Santana, R., H. Karshenas, C. Bielza, and P. Larrañaga, "Regularized k-order Markov Models in EDAs", Proceedings of the 2011 Genetic and Evolutionary Conference (GECCO-2011): ACM Digital Library, pp. 593–600, 2011.
Santana, R., H. Karshenas, C. Bielza, and P. Larrañaga, "Quantitative genetics in multi-objective optimization algorithms: From useful insights to effective methods", Proceedings of the 2011 Genetic and Evolutionary Conference (GECCO-2011): ACM Digital Library, pp. 91-92, 2011.
Vidaurre, D., C. Bielza, and P. Larrañaga, "On nonlinearity in neural encoding models applied to the primary visual cortex", Network: Computation in Neural Systems, vol. 22, no. 1-4, pp. 97-125, 2011.
Vidaurre, D., C. Bielza, and P. Larrañaga, "Forward Stagewise Naive Bayes", Progress in Artificial Intelligence, vol. In press, 2011.
Zaragoza, J. H., L. E. Sucar, E. F. Morales, C. Bielza, and P. Larrañaga, "Bayesian chain classifiers for multidimensional classification", Proceedings of the 22nd International Joint Conference on Artificial Intelligence (IJCAI’11): AAAI Press, pp. 2192–-2197, 2011.
2010
Bielza, C., M. Gómez, and P. Shenoy, "Modelling Challenges with Influence Diagrams: Constructing Probability and Utility Models", Decision Support Systems, vol. 49, pp. 354-364, 2010.
Bielza, C., G. Li, and P. Larrañaga, Multi-Dimensional classification with Bayesian networks, : Universidad Politécnica de Madrid. TR:UPM-FI/DIA/2010-1, 2010.
Bielza, C., J. A. Fernandez del Pozo, P. Larrañaga, and E. Bengoetxea, "Multidimensional Statistical Analysis of the Parameterization of a Genetic Algorithm for the Optimal Ordering of Tables", Expert Systems with Applications, vol. 37, pp. 804-815, 2010.
Borchani, H., C. Bielza, and P. Larrañaga, "Learning CB-decomposable multi-dimensional Bayesian network classifiers", Proceedings of the 5th European Workshop on Probabilistic Graphical Models (PGM’10), pp. 25-32, 2010.
Borchani, H., P. Larrañaga, and C. Bielza, "Mining Concept-Drifting Data Streams Containing Labeled and Unlabeled Instances", The Twenty Third International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems (IEA/AIE'10), vol. 1, pp. 531-540, 2010.
Correa, M., Inteligencia Artificial para Predicción y Control del Acabado Superficial en Procesos, , (supervised by Concha Bielza), Departamento de Inteligencia Artificial, Universidad Politécnica de Madrid, 2010.
Cuesta, I., C. Bielza, M. Cuenca-Estrella, P. Larrañaga, and J. L. Rodriguez-Tudela, "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, vol. 54, no. 4, pp. 1541-1546, 2010.
García, A., B. Suárez, M. Betanzos, G. M. López Vivanco, R. Armañanzas, I. Inza, and P. Larrañaga, Methods and kits for the diagnosis and the staging of colorectal cancer, , 2010.
Lopez-Cruz, P. L., C. Bielza, P. Larrañaga, R. Benavides-Piccione, and J. DeFelipe, Bayesian networks applied to the simulation and modelling of 3D basal dendritic trees from pyramidal neurons, , Universidad Politécnica de Madrid. Tech. Rep. UPM-FI/DIA/2010-2., 2010.
Miquelez, T., Avances en Algoritmos de Estimación de Distribuciones. Alternativas en el Aprendizaje y Representación de Problemas, , (supervised by Pedro Larrañaga), Departamento de Ciencias de la Computación e Inteligencia Artificial, Universidad del País Vasco, 2010.
Pérez, A., Supervised Classification in Continuous Domains with Bayesian Networks, , (supervised by Pedro Larrañaga), Departamento de Ciencias de la Computación e Inteligencia Artificial, Universidad del País Vasco, 2010.
Santana, R., P. Larrañaga, and J. A. Lozano, "Learning factorizations in estimation of distribution algorithms using affinity propagation", Evolutionary Computation, vol. in press, 2010.
Santana, R., C. Bielza, P. Larrañaga, J. A. Lozano, C. Echegoyen, A. Mendiburu, R. Armañanzas, and S. Shakya, "MATEDA-2.0: A Matlab Package for the Implementation and Analysis of Estimation of Distribution Algorithms", Journal of Statistical Software, vol. 35, no. 7, pp. 1-30, 2010.
Vidaurre, D., C. Bielza, and P. Larrañaga, "Learning an L1-regularized Gaussian Bayesian Network in the Equivalence Class Space", IEEE Transactions on Systems, Man and Cybernetics, Part B, vol. 40, no. 5, pp. 1231-1242, 2010.
2009
Armañanzas, R., B. Calvo, I. Inza, M. López-Hoyos, V. Martínez-Taboada, E. Ucar, I. Bernales, A. Fullaondo, P. Larrañaga, and A. M. Zubiaga, "Microarray analysis of autoimmune diseases by machine learning procedures", IEEE Transactions on Information Technology in Biomedicine, vol. 13, no. 3, pp. 341-350, 2009.
Armañanzas, R., Consensus Policies to Solve Bioinformatic Problems Through Bayesian Network Classifiers and Estimation of Distribution Algorithms, , (supervised by Pedro Larrañaga), Departamento de Ciencias de la Computación e Inteligencia Artificial, Universidad del País Vasco, 2009.
Bielza, C., M. Gómez, and P. Shenoy, Modelling Challenges with Influence Diagrams: Representation Issues, , no. 319: School of Business, University of Kansas, 2009.
Bielza, C., V. Robles, and P. Larrañaga, "Estimation of Distribution Algorithms as Logistic Regression Regularizers of Microarray Classifiers", Methods of Information in Medicine, vol. 48, no. 3, pp. 236-241, 2009.
Bielza, C., M. Gómez, and P. Shenoy, Modelling Challenges with Influence Diagrams: Constructing Probability and Utility Models, , no. 320: School of Business, University of Kansas, 2009.
Bielza, C., J. A. Fernandez del Pozo, P. Larrañaga, and E. Bengoetxea, Multidimensional statistical analysis of the parameterization of a genetic algorithm for the optimal ordering of tables, : Facultad de Informática (UPM). UPM.FI/DIA/2009-1, 2009.
Correa, M., C. Bielza, and J. Pamies-Teixeira, "Comparison of Bayesian Networks and Artificial Neural Networks for Quality Detection in a Machining Process", Expert Systems with Applications, vol. 36, pp. 7270-7279, 2009.
Correa, M., and C. Bielza, Explanation of a Bayesian Network Classifier by Means of Decision Trees, , no. UPM-FI-DIA: Universidad Politécnica de Madrid, 2009.
Cuesta, I., C. Bielza, P. Larrañaga, M. Cuenca-Estrella, F. Laguna, D. Rodríguez-Pardo, B. Almirante, A. Pahissa, and J. L. Rodriguez-Tudela, "Data Mining Validation of EUCAST Fluconazole Breakpoints Established by the European Committee on Antimicrobial Susceptibility Testing", Antimicrobial Agents and Chemotherapy, vol. 53, no. 7, pp. 2949-2954, 2009.
Diaz, E., E. Ponce-de-Leon, P. Larrañaga, and C. Bielza, "Probabilistic graphical Markov model learning: an adaptive strategy", MICAI, Lecture Notes in Artificial Intelligence, 5845, vol. 5845: Springer, pp. 225-236, 2009.
Ibañez, A., P. Larrañaga, and C. Bielza, "Predicting Citation Count of Bioinformatics Papers within Four Years of Publication", Bioinformatics, vol. 25, no. 24, pp. 3303-3309, 2009.
Inza, I., B. Calvo, R. Armañanzas, E. Bengoetxea, P. Larrañaga, and J. A. Lozano, "Machine learning: An indispensable tool in bioinformatics", Bioinformatics Methods in Clinical Research: Springer, pp. 25-48, 2009.
Pérez, A., P. Larrañaga, and I. Inza, "Bayesian classifiers based on kernel estimation: Flexible classifiers", International Journal of Approximate Reasoning, vol. 50, no. 2, pp. 341-362, 2009.
Romero, T., and P. Larrañaga, "Triangulation of Bayesian networks with recursive estimation of distribution algorithms", International Journal of Approximate Reasoning, vol. 50, no. 3, pp. 472-484, 2009.
Santana, R., C. Echegoyen, A. Mendiburu, C. Bielza, J. A. Lozano, P. Larrañaga, R. Armañanzas, and S. Shakya, MATEDA: A suite of EDA programs in Matlab, : Servicio de Publicaciones de la Facultad de Informática, UPV–EHU. EHU-KZAA-IK-2/09, 2009.
Santana, R., P. Larrañaga, and J. A. Lozano, Learning factorizations in estimation of distribution algorithms using affinity propagation, : Servicio de Publicaciones de la Facultad de Informática, UPV–EHU. EHU-KZAA-IK-1/08, 2009.
Santana, R., C. Bielza, J. A. Lozano, and P. Larrañaga, "Mining Probabilistic Models Learned by EDAs in the Optimization of Multi-Objective Problems", Proceedings of the 11th Annual Conference on Genetic and Evolutionary Computation: ACM, pp. 445-452, 2009.
Vidaurre, D., C. Bielza, and P. Larrañaga, "Variable Selection in Local Regression Models via an Iterative LASSO", The Eighth Workshop on Uncertainty Processing (WUPES'09), pp. 237-250, 2009.
Vidaurre, D., C. Bielza, and P. Larrañaga, Learning a L1-regularized Gaussian Bayesian network in the equivalence class space, : Facultad de Informática (UPM). UPM.FI/DIA/2009-2, 2009.
2008
Armañanzas, R., I. Inza, and P. Larrañaga, "Detecting reliable gene interactions by a hierarchy of Bayesian networks classifiers", Computer Methods and Programs in Biomedicine, vol. 91, pp. 110-121, 2008.
Armañanzas, R., Y. Saeys, I. Inza, M. García-Torres, Y. van de Peer, C. Bielza, and P. Larrañaga, "Mass spectrometry data analysis: it's all in the preprocessing", Proceedings of the Benelux Bioinformatics Conference, Maastricht, The Netherlands, pp. 92, 2008.
Bielza, C., J. A. Fernandez del Pozo, and P. Lucas, "Explaining Clinical Decisions by Extracting Regularity Patterns", Decision Support Systems, vol. 44, pp. 397-408, 2008.
Calvo, B., Positive Unlabelled Learning with Applications in Computational Biology, , (supervised by Pedro Larrañaga), Departamento de Ciencias de la Computación e Inteligencia Artificial, Universidad del País Vasco, 2008.
Correa, M., J. R. Alique, and C. Bielza, "Comparativa de Modelos con Aprendizaje Supervisado: Aplicación a un Proceso Industrial", IV Simposio de Control Inteligente, 2008.
Correa, M., C. Bielza, J. Pamies-Teixeira, and J. R. Alique, "Redes Bayesianas vs Redes Neuronales en Modelos para la Predicción del Acabado Superficial", XVII Congreso de Máquinas-Herramienta y Tecnologías de Fabricación, 2008.
Correa, M., C. Bielza, M. J. Ramírez, and J. R. Alique, "A Bayesian Network Model for Surface Roughness Prediction in the Machining Process", International Journal of Systems Science, vol. 39, no. 12, pp. 1181-1192, 2008.
Furney, S. J., B. Calvo, P. Larrañaga, J. A. Lozano, and N. López-Bigas, "Prioritization of candidate cancer genes-an aid to oncogenomic studies", Nucleic Acids Research, pp. 1-9, 2008.
Morales, D., E. Bengoetxea, P. Larrañaga, M. Garca, Y. Franco-Iriarte, M. Fresnada, and M. Merino, "Bayesian classification for the selection of in-vitro human embryos using morphological and clinical data", Computer Methods and Programs in Biomedicine, no. 90, pp. 104-116, 2008.
Morales, D., Modelos Gráficos Probabilísticos Aplicados a la Fecundación en Vitro, , (supervised by Pedro Larrañaga), Departamento de Ciencias de la Computación e Inteligencia Artificial, Universidad del País Vasco, 2008.
Morales, D., E. Bengoetxea, and P. Larrañaga, "Selection of human embryos for transfer by Bayesian classifiers", Computer in Biology and Medicine, vol. 38, pp. 1177-1186, 2008.
Robles, V., C. Bielza, P. Larrañaga, S. González, and L. Ohno-Machado, "Optimizing Logistic Regression Coefficients for Discrimination and Calibration Using Estimation of Distribution Algorithms", TOP, vol. 16, pp. 345-366, 2008.
Santafé, G., Advances on Supervised and Unsupervised Learning of Bayesian Networks Models. Applications to Population Genetics, , (supervised by Pedro Larrañaga), Departamento de Ciencias de la Computación e Inteligencia Artificial, Universidad del País Vasco, 2008.
Santafé, G., J. A. Lozano, and P. Larrañaga, "Inference of population structure using genetic markers and a Bayesian model averaging approach for clustering", Journal of Computational Biology, vol. 15, no. 2, pp. 207-220, 2008.
Santana, R., J. A. Lozano, and P. Larrañaga, "Protein folding in simplified models with estimation of distribution algorithms", IEEE Transactions on Evolutionary Computation, vol. 12, no. 4, pp. 418-438, 2008.
Santana, R., P. Larrañaga, and J. A. Lozano, "Combining variable neighborhood search and estimation of distribution algorithms", Journal of Heuristics, vol. 14, pp. 519-547, 2008.
Zipritia, I., J. Elorriaga, A. Arruarte, P. Larrañaga, and R. Armañanzas, "What is behind a summary evaluation decision?", Behavior Research Methods, vol. 2, no. 40, pp. 597-612, 2008.
2007
Armañanzas, R., B. Calvo, I. Inza, P. Larrañaga, I. Bernales, A. Fullaondo, and A. M. Zubiaga, "Bayesian Classifiers with Consensus Gene Selection: a case study in the Systemic Lupus Erythematosus", Progress in Industrial Mathematics at ECMI 2006, vol. 12: Springer, pp. 560-565, 2007.
Calvo, B., N. López-Bigas, S. J. Furney, P. Larrañaga, and J. A. Lozano, "A partially supervised approach to dominant and recessive human disease gene prediction", Computer Methods and Programs in Biomedicine, vol. 85, no. 3, pp. 229-237, 2007.
Calvo, B., J. A. Lozano, and P. Larrañaga, "Learning Bayesian classifiers from positive and unlabeled examples", Pattern Recognition Letters, vol. 28, no. 16, pp. 2375-2384, 2007.
Correa, M., M. J. Ramírez, C. Bielza, J. Pamies, and J. R. Alique, "Predicción de la Calidad Superficial Usando Modelos Probabilísticos", VII Congreso de la Asociación Colombiana de Automática, pp. 1-6, 2007.
Flores, J. L., I. Inza, and P. Larrañaga, "Wrapper discretization by means of estimation of distribution algorithms", Intelligent Data Analysis Journal, vol. 11, no. 5, pp. 525-546, 2007.
García, A., A. Freije, R. Armañanzas, I. Inza, Z. Ispizua, P. Heredia, P. Larrañaga, G. López Vivanco, T. Suárez, and M. Betanzos, "Gene expression model for the classification of human colorectal cancer and potential CRC biomarkers search", Drug Discovery Technology, London, UK, 2007.
Gómez, M., C. Bielza, J. A. Fernandez del Pozo, and S. Ríos-Insua, "A Graphical Decision-Theoretic Model for Neonatal Jaundice", Medical Decision Making, vol. 27, no. 3, pp. 250-265, 2007.
Miquelez, T., E. Bengoetxea, A. Mendiburu, and P. Larrañaga, "Combining Bayesian classifiers and estimation of distribution algorithms for optimization in continuous domains", Connection Science, vol. 19, no. 4, pp. 297-319, 2007.
Romero, T., Algoritmos de Estimación de Distribuciones Aplicados a Problemas Combinatorios en Modelos Gráficos Probabilísticos, , (supervised by Pedro Larrañaga), Departamento de Ciencias de la Computación e Inteligencia Artificial, Universidad del País Vasco, 2007.
Saeys, Y., I. Inza, and P. Larrañaga, "A review of feature selection techniques in bioinformatics", Bioinformatics, vol. 23, no. 19, pp. 2507-2517, 2007.
Santana, R., P. Larrañaga, and J. A. Lozano, "Side chain placement using estimation of distribution algorithms", Artificial Intelligence in Medicine, vol. 39, no. 1, pp. 49-63, 2007.
2006
Ballestero, E., C. Bielza, and D. Pla-Santamaría, "A Decision Approach to Competitive Electronic Sealed-Bid Auctions for Land", Journal of the Operational Research Society, vol. 57, pp. 1126-1133, 2006.
Correa, M., M. J. Ramírez, C. Bielza, and J. R. Alique, "Modelos Probabilísticos para la Predicción de la Rugosidad Superficial en Fresado a Alta Velocidad", XVI Congreso de Máquinas-Herramienta y Tecnologías de Fabricación, vol. 1, pp. 347-365, 2006.
Correa, M., C. Bielza, M. J. Ramírez, and J. Pamies, "Modelado y Predicción con Redes Probabilísticas. Caso de Estudio: La Rugosidad Superficial", XXVII Jornadas de Automática, pp. 1356-1361, 2006.
Fernandez del Pozo, J. A., Listas KBM2L para la Síntesis de Conocimiento en Sistemas de Ayuda a la Decisión, , (supervised by Concha Bielza), Facultad de Informática, Politécnica de Madrid, 2006.
García, A., A. Freije, R. Armañanzas, I. Inza, Z. Ispizua, P. Heredia, P. Larrañaga, G. López Vivanco, T. Suárez, and M. Betanzos, "Simultaneous Search of Genomic and Proteomic Biomarkers in Human Colorectal Cancer", Genomes to Systems Conference, Manchester, UK, 2006.
González, C., Contributions on Theoretical Aspects of Estimation of Distribution Algorithms, , (supervised by Pedro Larrañaga), Departamento de Ciencias de la Computación e Inteligencia Artificial, Universidad del País Vasco, 2006.
Larrañaga, P., B. Calvo, R. Santana, C. Bielza, J. Galdiano, I. Inza, J. A. Lozano, R. Armañanzas, G. Santafé, and A. Pérez, "Machine Learning in Bioinformatics", Briefings in Bioinformatics, vol. 17, no. 1, pp. 86-112, 2006.
Lozano, J. A., P. Larrañaga, P. Inza, and E. Bengoetxea, Towards a New Evolutionary Computation. Advances in Estimation of Distribution Algorithms, : Springer Verlag, 2006.
Pérez, A., P. Larrañaga, and I. Inza, "Supervised classification with conditional Gaussian networks: Increasing the structure complexity from naive Bayes", International Journal of Approximate Reasoning, vol. 43, pp. 1-25, 2006.
Santafé, G., J. A. Lozano, and P. Larrañaga, "Bayesian model averaging of naive Bayes for clustering", IEEE Transactions on Systems, Man, and Cybernetics, vol. 36, no. 5, pp. 1149-1161, 2006.
Santana, R., Advances in Probabilistic Graphical Models for Optimization and Learning. Applications in Protein Modelling, , (supervised by Pedro Larrañaga), Departamento de Ciencias de la Computación e Inteligencia Artificial, Universidad del País Vasc, 2006.
2005
Armañanzas, R., B. Calvo, I. Inza, P. Larrañaga, I. Bernales, A. Fullaondo, and A. M. Zubiaga, "Clasificadores Bayesianos con selección consensuada de genes en la predicción del lupus eritematoso sistémico", Minería de Datos: Técnicas y Aplicaciones: Ediciones Dpt. de Informática de la UCLM, pp. 107-135, 2005.
Armañanzas, R., B. Calvo, I. Inza, P. Larrañaga, I. Bernales, A. Fullaondo, and A. M. Zubiaga, "Selección de genes asociados a dos enfermedades autoinmunes a partir de microarrays de ADN", VI Jornadas de Transferencia Tecnológica de Inteligencia Artificial, TTIA (AEPIA), Granada, Spain, pp. 63-70, 2005.
Armañanzas, R., I. Inza, and P. Larrañaga, "Consensus Gene Selection on DNA Microarrays", European Conference on Computational Biology, Madrid, Spain, 2005.
Barreiro, P., M. Ruiz-Altisent, C. Bielza, and A. Moya-González, "Multivariate Analysis of an On-Line NIR Spectrometer under Industrial Use", Acta Horticulturae, vol. 674, no. 513-519: International Society for Horticultural Science, 2005.
Blanco, R., I. Inza, M. Merino, J. Quiroga, and P. Larrañaga, "Feature selection in Bayesian classifiers for the prognosis of survival of cirrhotic patients treated with TIPS", Journal of Biomedical Informatics, vol. 38, pp. 376–388, 2005.
Blanco, R., Learning Bayesian Networks from Data with Factorization and Classification Purposes. Applications in Biomedicine, , (supervised by Pedro Larrañaga), Departamento de Ciencias de la Computación e Inteligencia Artificial, Universidad del País Vasco, 2005.
Fernandez del Pozo, J. A., C. Bielza, and M. Gómez, "A List-Based Compact Representation for Large Decision Tables Management", European Journal of Operational Research, vol. 160, no. 3, pp. 638-662, 2005.
Larrañaga, P., and J. A. Lozano, "Special issue on estimation of distribution algorithms", Evolutionary Computation, vol. 13, no. 1, pp. v-vi, 2005.
Larrañaga, P., J. A. Lozano, J. M. Peña, and I. Inza, "Special issue on Probabilistic Graphical Models in Classification", Machine Learning, vol. 59, pp. 211-212, 2005.
Martín, J., C. Bielza, and D. Ríos Insua, "Approximating Nondominated Sets in Continuous Multiobjective Optimization Problems", Naval Research Logistics, vol. 52, no. 5, pp. 469-480, 2005.
Peña, J. M., J. A. Lozano, and P. Larrañaga, "Globally multimodal problem optimization via an estimation of distribution algorithm based on unsupervised learning of Bayesian networks", Evolutionary Computation, pp. 43-66, 2005.
Roberto, C., E. Bengoetxea, I. Bloch, and P. Larrañaga, "Inexact graph matching for model-based recognition: Evaluation and comparison of optimization algorithms", Pattern Recognition, vol. 38, pp. 2099–2113, 2005.
Santana, R., P. Larrañaga, and J. A. Lozano, Properties of Kikuchi approximations constructed from clique based decompositions, : Servicio de Publicaciones de la Facultad de Informática, UPV–EHU. EHU-KZAA-IK-2/05, 2005.
2004
Bielza, C., J. A. Fernandez del Pozo, and P. Lucas, "Research and Development in Intelligent Systems XX", Optimal Decision Explanation by Extracting Regularity Patterns: Springer, pp. 283-294, 2004.
Blanco, R., P. Larrañaga, I. Inza, and B. Sierra, "Gene selection for cancer classification using wrapper approaches", International Journal of Pattern Recognition and Artificial Intelligence, vol. 18, no. 8, pp. 1373-1390, 2004.
Fernandez del Pozo, J. A., and C. Bielza, "Sensitivity Analysis and Explanation of Optimal Decisions", Second European Workshop on Probabilistic Graphical Models, pp. 81-88, 2004.
Gómez, M., J. A. Fernandez del Pozo, C. Bielza, and S. Ríos-Insua, "Gestión de la Ictericia Neonatal", La Aventura de Decidir: Una Aproximación Científica mediante Casos Reales: Universidad de Málaga, pp. 73-94, 2004.
Gómez, M., and C. Bielza, "Node Deletion Sequences in Influence Diagrams Using Genetic Algorithms", Statistics {&} Computing, vol. 14, no. 3, pp. 181-198, 2004.
Inza, I., P. Larrañaga, R. Blanco, and A. J. Cerrolaza, "Filter versus wrapper gene selection approaches in DNA microarray domains", Artificial Intelligence in Medicine, no. 31, pp. 91-103, 2004.
Larrañaga, P., E. Menasalvas, J. M. Peña, and V. Robles, "Data mining in genomics and proteomics", Artificial Intelligence in Medicine, no. 31, pp. iii-iv, 2004.
Merino, M., Predicción de Mortalidad Precoz tras Implantación Percutánea Intrahepática en Pacientes Cirróticos. Aplicación de Métodos de Clasificación Supervisada, , (supervised by Pedro Larrañaga), Departamento de Medicina Interna, Universidad de Navarra, 2004.
Miquelez, T., E. Bengoetxea, and P. Larrañaga, Applying Bayesian classifiers to evolutionary computation, : Servicio de Publicaciones de la Facultad de Informática, UPV–EHU. KAT-IK-04-01, 2004.
Miquelez, T., E. Bengoetxea, and P. Larrañaga, "Evolutionary computation based on Bayesian classifiers", International Journal of Applied Mathematics and Computer Science, vol. 14, no. 3, pp. 101–115, 2004.
Owodunni, O. O., J. Diaz-Rozo, and S. Hinduja, "Development and Evaluation of a Low-Cost Computer Controlled Reconfigurable Rapid Tool", Computer-Aided Design and Applications, vol. 1, issue 1-4, pp. 101--108, 2004.
Peña, J. M., J. A. Lozano, and P. Larrañaga, "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, vol. 12, pp. 63-82, 2004.
Puch, R. O., J. Q. Smith, and C. Bielza, "Hierarchical Junction Trees: Conditional Independence Preservation and Forecasting in Dynamic Bayesian Networks with Heterogeneous Evolution", Advances in Bayesian Networks Studies in Fuzziness and Soft Computing: Springer, pp. 57-76, 2004.
Ríos-Insua, S., A. Mateos, C. Bielza, and A. Jimenez, Investigación Operativa. Modelos Determinísticos y Estocásticos, : Centro de Estudios Ramón Areces, 2004.
Robles, V., P. Larrañaga, J. M. Peña, E. Menasalvas, M. S. Pérez, and V. Herves, "Bayesian networks as consensed voting system in the construction of a multi–classifier for protein secondary structure prediction", Artificial Intelligence in Medicine, no. 31, pp. 117–136, 2004.
Romero, T., P. Larrañaga, and B. Sierra, "Learning Bayesian networks in the space of orderings with estimation of distribution algorithms", International Journal of Pattern Recognition and Artificial Intelligence, vol. 18, no. 4, pp. 607–625, 2004.
Santafé, G., J. A. Lozano, and P. Larrañaga, El Algoritmo TM para Clasificadores Bayesianos, : Servicio de Publicaciones de la Facultad de Informática, UPV–EHU. EHU-KZAA-IK-2/04, 2004.
Santafé, G., J. A. Lozano, and P. Larrañaga, Full Bayesian model averaging of naive Bayes for clustering, : Servicio de Publicaciones de la Facultad de Informática, UPV–EHU. EHU-KZAA-IK-3/04, 2004.
2003
Ballestero, E., J. M. Antón, and C. Bielza, "Compromise-Based Approach to Road Project Selection in Madrid Metropolitan Area", Journal of the Operations Research Society of Japan, vol. 46, no. 1, pp. 99-122, 2003.
Barreiro, P., R. Alonso, E. C. Correa, M. Ruiz-Altisent, J. C. Fabero, L. Casasus, M. Calles, and C. Bielza, "Simulation of Gases in Fruit Storage Chambers with Lattice Boltzman", Acta Horticulturae, vol. 599: International Society for Horticultural Science, pp. 413-419, 2003.
Bielza, C., and S. Ríos-Insua, "Análisis de Decisiones Clínicas", Manual de Informática Médica: Menarini - Caduceo Multimedia, pp. 467-491, 2003.
Bielza, C., P. Barreiro, M. I. Rodríguez-Galiano, and J. Martín, "Logistic Regression for Simulating Damage Occurrence on a Fruit Grading Line", Computers {&} Electronics in Agriculture, vol. 38, no. 2, pp. 95-113, 2003.
Bielza, C., J. A. Fernandez del Pozo, and P. Lucas, "Finding and Explaining Optimal Treatments", Lecture Notes in Artificial Intelligence: Springer, pp. 299-303, 2003.
Blanco, R., I. Inza, and P. Larrañaga, "Learning Bayesian networks in the space of structures by estimation of distribution algorithms", International Journal of Intelligent Systems, vol. 18, pp. 205-220, 2003.
González, C., D. J. Rodriguez, J. A. Lozano, and P. Larrañaga, "Analysis of the univariate marginal distribution algorithm modeled by Markov chains", Lecture Notes in Computer Science, pp. 510–517, 2003.
Robles, V., P. Larrañaga, J. M. Peña, E. Menasalvas, and M. S. Pérez, "Interval estimation naïve Bayes", Lecture Notes in Computer Science, pp. 143–154, 2003.
Robles, V., Clasificación Supervisada basada en Redes Bayesianas. Aplicación en Biología Computacional, , (supervised by Pedro Larrañaga), Departamento de Arquitectura y Tecnología de Sistemas Informáticos, Universidad Politécnica de Madrid, 2003.
Robles, V., P. Larrañaga, J. M. Peña, O. Marban, J. Crespo, and M. S. Pérez, "Collaborative filtering using interval estimation naïve Bayes", Lecture Notes in Artificial Intelligence, pp. 46–53, 2003.
Santafé, G., J. A. Lozano, and P. Larrañaga, "Fitting mixture models with estimation of distribution algorithms", Actas del II Congreso Español sobre Metaheurísticas, Algoritmos Evolutivos y Bioinspirados, pp. 232–236, 2003.
2002
Bengoetxea, E., Inexact Graph Matching Using Estimation of Distribution Algorithms, , (supervised by Pedro Larrañaga), Département Traitement du Signal et des Images, Ecole Nationale Supérieure de Télécomunications, 2002.
Bengoetxea, E., P. Larrañaga, I. Bloch, A. Perchant, and C. Boeres, "Inexact graph matching by means of estimation of distribution algorithms", Pattern Recognition, vol. 35, no. 12, pp. 2867–2880, 2002.
Bengoetxea, E., P. Larrañaga, I. Bloch, and A. Perchant, "Solving graph matching with EDAs using a permutation–based representation", Estimation of Distribution Algorithms. A New Tool for Evolutionary Computation, pp. 243–265, 2002.
Bielza, C., and J. A. Fernandez del Pozo, "An Interactive Framework for Open Queries in Decision Support Systems", Lecture Notes in Artificial Intelligence: Springer, pp. 254-264, 2002.
Cotta, C., E. Alba, R. Sagarna, and P. Larrañaga, "Adjusting weights in artificial neural networks using evolutionary algorithms", Estimation of Distribution Algorithms. A New Tool for Evolutionary Computation, pp. 361–377, 2002.
de Campos, L. M., J. A. Gamez, P. Larrañaga, S. Moral, and T. Romero, "Partial abductive inference in Bayesian networks: an empirical comparison between GAs and EDAs", Estimation of Distribution Algorithms. A New Tool for Evolutionary Computation, pp. 323–341, 2002.
Fernandez del Pozo, J. A., and C. Bielza, "New Structures for Conditional Probability Tables", First European Workshop on Probabilistic Graphical Models: Univ. de Castilla-La Mancha, pp. 61-70, 2002.
Gómez, M., IctNeo: Un Sistema de Ayuda a la Decisión para el Tratamiento de la Ictericia, , (supervised by Concha Bielza), Departamento de Inteligencia Artificial, Universidad Politécnica de Madrid, 2002.
González, C., J. A. Lozano, and P. Larrañaga, "Mathematical modelling of UMDAc algorithm with tournament selection. Behaviour on linear and quadratic functions", International Journal of Approximate Reasoning, vol. 31, pp. 313–340, 2002.
González, C., J. A. Lozano, and P. Larrañaga, "Modelado matemático del algoritmo UMDAc con selección por torneo aplicado a funciones lineales", Primer Congreso Español de Algoritmos Evolutivos y Bioinspirados, pp. 437–444, 2002.
González, C., J. A. Lozano, and P. Larrañaga, "Mathematical modeling of discrete estimation of distribution algorithms", Estimation of Distribution Algorithms. A New Tool for Evolutionary Computation, pp. 147–163, 2002.
Inza, I., P. Larrañaga, and B. Sierra, "Estimation of distribution algorithms for feature subset selection in large dimensionality domains", Data Mining: A Heuristic Approach, pp. 97–116, 2002.
Inza, I., P. Larrañaga, and B. Sierra, "Feature weighting for nearest neighbor by estimation of distribution algorithms", Estimation of Distribution Algorithms. A New Tool for Evolutionary Computation, pp. 295–311, 2002.
Inza, I., Advances in Supervised Classification Based on Probabilistic Graphical Models, , (supervised by Pedro Larrañaga), Departamento de Ciencias de la Computación e Inteligencia Artificial, Universidad del País Vasco, 2002.
Inza, I., P. Larrañaga, and B. Sierra, "Feature subset selection by estimation of distribution algorithms", Estimation of Distribution Algorithms. A New Tool for Evolutionary Computation, pp. 269–293, 2002.
Inza, I., B. Sierra, R. Blanco, and P. Larrañaga, "Gene selection by sequential search wrapper approaches in microarray cancer class prediction", Journal of Intelligent and Fuzzy Systems, vol. 12, no. 1, pp. 25-33, 2002.
Larrañaga, P., and J. A. Lozano, Estimation of Distribution Algorithms. A New Tool for Evolutionary Computation, : Kluwer Academic Publishers, 2002.
Larrañaga, P., "An introduction to probabilistic graphical models", Estimation of Distribution Algorithms. A New Tool for Evolutionary Computation, pp. 27–56, 2002.
Larrañaga, P., "A review on estimation of distribution algorithms", Estimation of Distribution Algorithms. A New Tool for Evolutionary Computation, pp. 57–100, 2002.
Larrañaga, P., and J. A. Lozano, "Synergies between evolutionary computation and probabilistic graphical models", International Journal of Approximate Reasoning, vol. 31, pp. 155–156, 2002.
Lozano, J. A., R. Sagarna, and P. Larrañaga, "Parallel estimation of distribution algorithms", Estimation of Distribution Algorithms. A New Tool for Evolutionary Computation, pp. 129–145, 2002.
Peña, J. M., J. A. Lozano, and P. Larrañaga, "Benefits of data clustering in multimodal function optimization via EDAs", Estimation of Distribution Algorithms. A New Tool for Evolutionary Computation, 2002.
Peña, J. M., J. A. Lozano, and P. Larrañaga, "Learning recursive Bayesian multinets for clustering by means of constructive induction", Machine Learning, vol. 47, pp. 63-89, 2002.
Puch, R. O., J. Q. Smith, and C. Bielza, "Inferentially Efficient Propagation in Non-Decomposable Bayesian Networks with Hierarchical Junction Trees", First European Workshop on Probabilistic Graphical Models: Univ. de Castilla-La Mancha, pp. 152-160, 2002.
Ríos-Insua, S., C. Bielza, and A. Mateos, Fundamentos de los Sistemas de Ayuda a la Decisión, : Ra-Ma, 2002.
Robles, V., P. de Miguel, and P. Larrañaga, "Solving the traveling salesman problem with EDAs", Estimation of Distribution Algorithms. A New Tool for Evolutionary Computation, pp. 211–229, 2002.
Roure, J., P. Larrañaga, and R. Sangüesa, "An empirical comparison between K-means, GAs and EDAs in partitional clustering", Estimation of Distribution Algorithms. A New Tool for Evolutionary Computation, pp. 343–360, 2002.
Sagarna, R., and P. Larrañaga, "Solving the 0–1 knapsack problem with EDAs", Estimation of Distribution Algorithms. A New Tool for Evolutionary Computation, pp. 195–209, 2002.
Sierra, B., E. A. Jimenez, I. Inza, P. Larrañaga, and J. Muruzábal, "Rule induction by estimation of distribution algorithms", Estimation of Distribution Algorithms. A New Tool for Evolutionary, pp. 313–322, 2002.
2001
Barreiro, P., F. García, M. Ruiz-Altisent, and C. Bielza, "Desarrollo de un Instrumento de Ayuda a la Decisión para la Mejora de las Líneas de Confección", Actas de Horticultura 28, IV Congreso Ibérico de Ciencias Hortícolas, vol. 1, pp. 61-69, 2001.
Barreiro, P., J. C. Fabero, C. Bielza, S. Bielza, R. Sanz, E. Correa, and M. Ruiz-Altisent, "Simulación de Gases en Cámaras de Almacenamiento de Fruta", 1er Congreso Nacional de Ingeniería para la Agricultura y el Medio Rural, vol. 1, pp. 321-327, 2001.
Bengoetxea, E., P. Larrañaga, I. Bloch, and A. Perchant, "Estimation of distribution algorithms: a new evolutionary computation approach for graph matching problems", Lecture Notes in Computer Science, pp. 454–468, 2001.
Bengoetxea, E., T. Miquelez, P. Larrañaga, and J. A. Lozano, "Experimental results in function optimization with EDAs in continuous domains", Estimation of Distribution Algorithms. A New Tool for Evolutionary Computation, pp. 181–194, 2001.
Bengoetxea, E., P. Larrañaga, I. Bloch, A. Perchant, and C. Boeres, Inexact graph matching using learning and simulation of probabilistic graphical models, : Ecole Nationale Supérieure des Télécomunications, Paris. 2001D017, 2001.
Bielza, C., S. Ríos-Insua, M. Gómez, and J. A. Fernandez del Pozo, "Sensitivity Analysis in IctNeo", Third International Symposium on Sensitivity Analysis of Model Output: CIEMAT, pp. 287-291, 2001.
Blanco, R., I. Inza, and P. Larrañaga, "Learning Bayesian networks from data by novel population–based, stochastic search algorithms", IX Conferencia de la Asociación Española para la Inteligencia Artificial, pp. 1095–1104, 2001.
Blanco, R., I. Inza, and P. Larrañaga, Learning Bayesian networks structures by estimation of distribution algorithms. An empirical comparison among four initializations, : Servicio de Publicaciones de la Facultad de Informática, UPV–EHU. EHU-KZAA-IK-2-01, 2001.
Fernandez del Pozo, J. A., C. Bielza, and M. Gómez, "Knowledge Synthesis Optimising the Combinatorial Storage of Multidimensional Matrices", XIXth EURO Summer Institute -Decision Analysis and Artificial Intelligence-, pp. 49-57, 2001.
Fernandez del Pozo, J. A., and C. Bielza, "Knowledge Synthesis on Multidimensional Matrices", Operational Research Peripatetic Postgraduate Programme, pp. 1-13, 2001.
González, C., J. A. Lozano, and P. Larrañaga, "The convergence behavior of the PBIL algorithm: A preliminary approach", International Conference in Artificial Neural Networks and Genetic Algorithms, pp. 228–231, 2001.
Inza, I., P. Larrañaga, and B. Sierra, "Feature subset selection by Bayesian networks: a comparison with genetic and sequential algorithms", International Journal of Approximate Reasoning, vol. 27, pp. 143–164, 2001.
Inza, I., M. Merino, P. Larrañaga, J. Quiroga, B. Sierra, and M. Girala, "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, vol. 23, no. 2, pp. 187–205, 2001.
Martín, J., and C. Bielza, "Aplicación de Técnicas de Simulación al Análisis de Decisiones: Estudio de una Línea de Clasificación de Frutas", Gestao da Tecnologia Empresarial e da Informacao: Conceitos e Estudos de Casos: Editora Internet, pp. 181-194, 2001.
Miquelez, T., E. Bengoetxea, I. Morlan, and P. Larrañaga, "Obtención de filtros para restauración de imágenes por medio de algoritmos de estimación de distribuciones", IX Conferencia de la Asociación Española para la Inteligencia Artificial, pp. 1145–1154, 2001.
Peña, J. M., On Unsupervised Learning of Bayesian Networks and Conditional Gaussian Networks, , (supervised by Pedro Larrañaga), Departamento de Ciencias de la Computación e Inteligencia Artificial, Universidad del País Vasco, 2001.
Peña, J. M., J. A. Lozano, and P. Larrañaga, "Performance evaluation of compromise conditional Gaussian networks for data clustering", International Journal of Approximate Reasoning, vol. 28, pp. 23-50, 2001.
Peña, J. M., J. A. Lozano, P. Larrañaga, and I. Inza, "Dimensionality reduction in unsupervised learning of conditional Gaussian networks", IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 23, no. 6, pp. 590–603, 2001.
Sierra, B., I. Inza, and P. Larrañaga, "On applying supervised classification techniques in medicine", Lecture Notes in Computer Sciences, pp. 14–19, 2001.
Sierra, B., N. Serrano, P. Larrañaga, E. J. Plasencia, I. Inza, J. J. Jiménez, P. Revuelta, and M. L. Mora, "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, vol. 22, pp. 233-248, 2001.
Sierra, B., E. Lazkano, I. Inza, M. Merino, P. Larrañaga, and J. Quiroga, "Prototype selection and feature subset selection by estimation of distribution algorithms. A case study in the survival of cirrhotic patients treated with TIPS", Lecture Notes in Artificial Intelligence, pp. 20-29, 2001.
2000
Ballestero, E., J. M. Antón, and C. Bielza, "Bayesian Approach to Road Selection with Compromise Utility Functions", 8th International Conference ``Information Processing and Management of Uncertainty in Knowledge-based Systems'', vol. 2, pp. 813-820, 2000.
Bielza, C., M. Gómez, S. Ríos-Insua, and J. A. Fernandez del Pozo, "Structural, Elicitation and Computational Issues Faced when Solving Complex Decision Making Problems with Influence Diagrams", Computers and Operations Research, vol. 27, no. 7-8, pp. 725-740, 2000.
Bielza, C., S. Ríos-Insua, M. Gómez, and J. A. Fernandez del Pozo, "Sensitivity Analysis in IctNeo", Robust Bayesian Analysis, Lecture Notes in Statistics: Springer, pp. 317-334, 2000.
Bielza, C., P. Barreiro, M. I. Rodríguez-Galiano, and J. Martín, "Logistic Regression for Simulating Damage Ocurrence on a Fruit Grading Line", Congreso Latinoiberoamericano de Investigación de Operaciones y Sistemas, pp. 49-50, 2000.
Gómez, M., and C. Bielza, "Node Deletion Sequences in Influence Diagrams using Genetic Algorithms", 8th International Conference ``Information Processing and Management of Uncertainty in Knowledge-based Systems'', vol. 3, pp. 1291-1298, 2000.
Gómez, M., S. Ríos-Insua, C. Bielza, and J. A. Fernandez del Pozo, "Multiattribute Utility Analysis in the IctNeo System", Research and Practice in Multiple Criteria: Springer, pp. 81-92, 2000.
González, C., J. A. Lozano, and P. Larrañaga, "Analyzing the population based incremental learning algorithm by means of discrete dynamical systems", Complex Systems, vol. 12, no. 4, pp. 465–479, 2000.
Inza, I., M. Merino, P. Larrañaga, J. Quiroga, B. Sierra, and M. Girala, "Feature subset selection using probabilistic tree structures. A case study in the survival of cirrhotic patients treated with TIPS", Lecture Notes in Computer Science, pp. 97-100, 2000.
Inza, I., P. Larrañaga, and B. Sierra, Feature weighting for nearest neighbor by estimation of Bayesian networks algorithms, : Servicio de Publicaciones de la Facultad de Informática, UPV–EHU. EHU-KZAA-IK-3-00, 2000.
Inza, I., P. Larrañaga, R. Etxeberria, and B. Sierra, "Feature subset selection by Bayesian network–based optimization", Artificial Intelligence, vol. 123, pp. 157-184, 2000.
Larrañaga, P., R. Etxeberria, and J. A. Lozano, "Combinatorial optimization by learning and simulation of Bayesian networks", Uncertainty in Artificial Intelligence, pp. 343–352, 2000.
Lozano, J. A., C. González, P. Larrañaga, and I. Inza, Analyzing the PBIL algorithm by means of discrete dynamical systems, : Servicio de Publicaciones de la Facultad de Informática, UPV–EHU. EHU-KZAA-IK-2-00, 2000.
Peña, J. M., J. A. Lozano, and P. Larrañaga, "An improved Bayesian structural EM algorithm for learning Bayesian networks for clustering", Pattern Recognition Letters, vol. 21, no. 8, pp. 779-786, 2000.
Ríos-Insua, S., M. Gómez, C. Bielza, and J. A. Fernandez del Pozo, "Implementation of IctNeo: a Decision Support System for Jaundice Management", Operations Research Proceedings, pp. 554-559, 2000.
Sierra, B., Aportaciones Metodológicas a la Clasificación Supervisada, , (supervised by Pedro Larrañaga), Departamento de Ciencias de la Computación e Inteligencia Artificial, Universidad del País Vasco, 2000.
Sierra, B., I. Inza, and P. Larrañaga, "Medical Bayes networks", Lecture Notes in Computer Science, pp. 4-14, 2000.
Sierra, B., I. Inza, and P. Larrañaga, Inteligencia computacional aplicada a la predicción del voto en encuestas electorales, : Servicio de Publicaciones de la Facultad de Informática, UPV–EHU. EHU-KZAA-IK-1-00, 2000.
1999
Ballestero, E., C. Bielza, M. Gómez, J. A. Maldonado, and P. Ballbe, Economía de la Salud, Estadística para Médicos, Clínica Asistida, : Dossat 2000, 1999.
Bielza, C., P. Müller, and D. Ríos Insua, "Decision Analysis by Augmented Probability Simulation", Management Science, vol. 45, no. 7, pp. 995-1007, 1999.
Bielza, C., and P. P. Shenoy, "A Comparison of Graphical Techniques for Asymmetric Decision Problems", Management Science, vol. 45, no. 11, 1999.
Dizdarevich, S., P. Larrañaga, J. M. Peña, B. Sierra, M. J. Gallego, and J. A. Lozano, "Predicción del fracaso empresarial mediante la combinación de clasificadores provenientes de la estadística y el aprendizaje automático", Tecnologías Inteligentes para la Gestión Empresarial, pp. 71–114, 1999.
Gómez, M., and C. Bielza, Algoritmo Genético para Secuencias de Eliminación de Nodos en Diagramas de Influencia, , vol. 1, pp. 116-124, 1999.
González, C., J. A. Lozano, and P. Larrañaga, "Algoritmo PBIL: un análisis teórico preliminar", Gráficas Espinardo S. L., pp. 81–88, 1999.
González, C., J. A. Lozano, and P. Larrañaga, The convergence behavior of PBIL algorithm: a preliminar approach, : Servicio de Publicaciones de la Facultad de Informática, UPV–EHU. EHU-KZAA-IK-3-99, 1999.
Inza, I., P. Larrañaga, R. Etxeberria, and B. Sierra, Feature subset selection by Bayesian networks based optimization, : Servicio de Publicaciones de la Facultad de Informática, UPV–EHU. EHU-KZAA-IK-2-99, 1999.
Inza, I., P. Larrañaga, B. Sierra, R. Etxeberria, J. A. Lozano, and J. M. Peña, "Representing the behaviour of supervised classification learning algorithms by Bayesian networks", Pattern Recognition Letters, vol. 20, no. 11-13, pp. 1201-1209, 1999.
Inza, I., M. Merino, P. Larrañaga, J. Quiroga, B. Sierra, and L. Girala, Feature subset selection by population–based incremental learning. A case study in the survival of cirrhotic patients treated with TIPS, : Servicio de Publicaciones de la Facultad de Informática, UPV–EHU. EHU-KZAA-IK-1-99, 1999.
Larrañaga, P., and C. M. H. Kuijpers, "Moral graph (triangulation of)", Encyclopedia of Statistical Sciences. Update Volume 3, pp. 462–464, 1999.
Larrañaga, P., R. Etxeberria, J. A. Lozano, and J. M. Peña, Optimization by learning and simulation of Bayesian and Gaussian networks, : Servicio de Publicaciones de la Facultad de Informática, UPV–EHU. EHU-KZAA-IK-4-99, 1999.
Larrañaga, P., C. M. H. Kuijpers, R. H. Murga, I. Inza, and S. Dizdarevich, "Genetic algorithms for the travelling salesman problem: A review of representations and operators", Artificial Intelligence Review, vol. 13, pp. 129-170, 1999.
Lozano, J. A., P. Larrañaga, M. Graña, and F. X. Albizuri, "Genetic algorithms: bridging the convergence gap", Theoretical Computer Science, vol. 229, pp. 11-22, 1999.
Lozano, J. A., and P. Larrañaga, "Applying genetic algorithms to search for the best hierarchical clustering of a dataset", Pattern Recognition Letters, vol. 20, no. 9, pp. 911-918, 1999.
Mateos, A., S. Ríos-Insua, C. Bielza, M. Gómez, M. Sánchez, and D. Blanco, "A Decision Analysis Approach to Extracorporeal Life Support", 5th International Conference of the Decision Sciences Institute, Integrating Technology and Human Decisions: Global Bridges into the 21st Century, pp. 665-667, 1999.
Peña, J. M., J. A. Lozano, and P. Larrañaga, "An empirical comparison of four initialization methods for the k-means algorithm", Pattern Recognition Letters, vol. 20, pp. 1027-1040, 1999.
Peña, J. M., J. A. Lozano, and P. Larrañaga, "Learning Bayesian networks for clustering by means of constructive induction", Pattern Recognition Letters, vol. 20, no. 11-13, pp. 1219-1230, 1999.
Sierra, B., N. Serrano, P. Larrañaga, E. J. Plasencia, I. Inza, J. J. Jiménez, J. M. de la Rosa, and M. L. Mora, "Machine learning inspired approaches to combine standard medical measures at an intensive care unit", Lecture Notes in Artificial Intelligence 1620, pp. 366–371, 1999.
1998
Bielza, C., and P. Shenoy, A Comparison of Graphical Techniques for Asymmetric Decision Problems: Supplement to Management Science Paper, , no. 282: School of Business, University of Kansas, 1998.
Bielza, C., and D. Ríos Insua, "Modelos Gráficos para la Toma de Decisiones", Sistemas Expertos Probabilísticos Colección Ciencia y Técnica: Eds. de la Universidad de Castilla - La Mancha, pp. 163-185, 1998.
Bielza, C., and D. Ríos Insua, Modelos Gráficos para la Toma de Decisiones, , no. 98-07: Universidad Rey Juan Carlos, 1998.
Inza, I., P. Larrañaga, B. Sierra, and M. Niño, Combination of classifiers. A case study in oncology, : Servicio de Publicaciones de la Facultad de Informática, UPV–EHU. EHU-KZAA-IK-1-98, 1998.
Larrañaga, P., "Aprendizaje automático de modelos gráficos II. Aplicaciones a la clasificación supervisada", Sistemas Expertos Probabilísticos, pp. 141–162, 1998.
Lozano, J. A., P. Larrañaga, and M. Graña, "Data Science Classification and Related Methods: Partitional cluster analysis with genetic algorithms: searching for the number of clusters", Studies in Classification, Data Analysis and Knowledge Organization, pp. 117–124, 1998.
Lozano, J. A., Algoritmos Genéticos Aplicados a la Clasificación no Supervisada, , (supervised by Pedro Larrañaga), Departamento de Ciencias de la Computación e Inteligencia Artificial, Universidad del País Vasco, 1998.
Ríos Insua, D., C. Bielza, J. Martín, and K. A. Salewicz, "Intelligent Decision Support for Reservoir Operations", Applied Decision Analysis: Kluwer, pp. 63-72, 1998.
Ríos-Insua, S., C. Bielza, C. Gómez, J. A. Fernandez del Pozo, M. Sánchez Luna, and S. Caballero, "An Intelligent Decision System for Jaundice Management in Newborn Babies", Applied Decision Analysis: Kluwer, pp. 133-144, 1998.
Sierra, B., and P. Larrañaga, "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, vol. 14, no. 1-2, pp. 215-230, 1998.
Vidakovic, B., and C. Bielza Lozoya, "On Time-Dependent Wavelet Denoising", IEEE Transactions on Signal Processing, vol. 46, no. 9, pp. 2549-2554, 1998.
1997
Albizuri, X., A. D’Anjou, M. Graña, and P. Larrañaga, "Structure of the high-order Boltzman machine from independence maps", IEEE Transactions on Neural Networks, vol. 8, no. 6, pp. 1351-1358, 1997.
Bielza, C., P. Müller, and D. Ríos Insua, "Markov Chain Monte Carlo Methods for Decision Analysis", 6th International Workshop on Artificial Intelligence and Statistics, pp. 31-38, 1997.
Bielza, C., and P. P. Shenoy, "A Comparison of Decision Trees, Influence Diagrams and Valuation Networks for Asymmetric Decision Problems", 6th International Workshop on Artificial Intelligence and Statistics, pp. 39-46, 1997.
Dizdarevich, S., F. Lizarraga, P. Larrañaga, B. Sierra, and M. J. Gallego, "Statistical and machine learning methods in the prediction of bankruptcy", Intelligent Technologies in Accounting and Business, pp. 85–100, 1997.
Etxeberria, R., P. Larrañaga, and J. M. Pikaza, "Analysis of the behaviour of genetic algorithms when learning Bayesian network structure from data", Pattern Recognition Letters, vol. 18, no. 11-13, pp. 1269-1273, 1997.
Larrañaga, P., B. Sierra, M. J. Gallego, M. J. Michelena, and J. M. Pikaza, "Learning Bayesian networks by genetic algorithms: A case study in the prediction of survival in malignant skin melanoma", Lecture Notes in Artificial Intelligence 1211, pp. 261–272, 1997.
Larrañaga, P., M. J. Gallego, B. Sierra, L. Urkola, and M. J. Michelena, "Bayesian networks, rule induction and logistic regression in the prediction of the survival of women survival suffering from breast cancer", Lecture Notes in Artificial Intelligence 1323, pp. 303–308, 1997.
Larrañaga, P., C. M. H. Kuijpers, M. Poza, and R. H. Murga, "Decomposing Bayesian networks: triangulation of the moral graph with genetic algorithms", Statistics and Computing, vol. 7, no. 1, pp. 19-34, 1997.
Ríos Insua, D., K. A. Salewicz, P. Müller, and C. Bielza, "Bayesian Methods in Reservoir Operations: the Zambezi River Case", The Practice of Bayesian Analysis: Arnold, pp. 107-130, 1997.
Ríos Insua, D., C. Bielza, J. Martín, and K. Salewicz, "BayRes: a System for Stochastic Multiobjective Reservoir Operations", Lecture Notes in Economics and Mathematical, pp. 319-327, 1997.
Sierra, B., and P. Larrañaga, "Searching for the optimal Bayesian network in classification tasks by genetic algorithms", 4th Workshop on Uncertainty Processing, pp. 144–155, 1997.
1996
Bielza, C., D. Ríos Insua, and S. Ríos-Insua, "Influence Diagrams under Partial Information", Bayesian Statistics 5: Oxford U.P., pp. 491-497, 1996.
Bielza, C., and B. Vidakovic, Time Adaptive Wavelet Denoising, , no. 1996-24: Duke University, 1996.
Larrañaga, P., B. Sierra, M. J. Gallego, and M. J. Michelena, "Predicción de la supervivencia en cáncer de mama via redes Bayesianas inducidas por algoritmos genéticos", XIV Congreso Anual de la Sociedad Española de Ingeniería Biomédica, pp. 197–199, 1996.
Larrañaga, P., M. Poza, Y. Yurramendi, R. H. Murga, and C. M. H. Kuijpers, "Structure learning of Bayesian networks by genetic algorithms: A performance analysis of control parameters", IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 18, no. 9, pp. 912-926, 1996.
Larrañaga, P., R. H. Murga, M. Poza, and C. M. H. Kuijpers, "Structure learning of Bayesian networks by hybrid genetic algorithms", Lecture Notes in Statistics 112, pp. 165–174, 1996.
Larrañaga, P., B. Sierra, M. J. Gallego, and M. J. Michelena, "Bayesian networks induced by genetic algorithms in the prediction of the survival of breast cancer", International Conference on Intelligent Technologies in Human-Related Sciences, pp. 259–266, 1996.
Larrañaga, P., C. M. H. Kuijpers, R. H. Murga, and Y. Yurramendi, "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, vol. 26, no. 4, pp. 487-493, 1996.
Larrañaga, P., C. M. H. Kuijpers, R. H. Murga, Y. Yurramendi, M. Graña, J. A. Lozano, X. Albizuri, A. D’Anjou, and F. J. Torrealdea, "Genetic algorithms applied to Bayesian networks", Computational Learning and Probabilistic Reasoning, pp. 211–234, 1996.
Ríos Insua, D., K. A. Salewicz, P. Müller, and C. Bielza, Bayesian Methods in Reservoir Operations: The Zambezi River Case, , no. 1996-30: Duke University, 1996.
1994
Larrañaga, P., and M. Poza, "Structure learning of Bayesian networks by genetic algorithms", New Approaches in Classification and Data Analysis, pp. 300–307, 1994.
Larrañaga, P., C. M. H. Kuijpers, M. Poza, and R. Murga, Optimal decomposition of Bayesian networks by genetic algorithms, : Servicio de Publicaciones de la Facultad de Informática, UPV–EHU. EHU-KZAA-IK-3-94, 1994.
Larrañaga, P., C. M. H. Kuijpers, and R. Murga, Tackling the travelling salesman problem with evolutionary algorithms: representations and operators, : Servicio de Publicaciones de la Facultad de Informática, UPV–EHU. EHU-KZAA-IK-3-94, 1994.
Larrañaga, P., M. Poza, J. A. Diego, and E. Arnaez, Ayuda al diagnóstico de la respuesta a un programa de rehabilitación de toxicómanos, a través de redes causales probabilísticas y árboles de clasificación inducidos por algoritmos genéticos, : Servicio de Publicaciones de la Facultad de Informática, UPV–EHU. EHU-KZAA-IK-4-94, 1994.
Ríos-Insua, S., A. Mateos, and C. Bielza, "Teoría de la Utilidad e Inteligencia Artificial", Fronteras de la Informática: Real Academia de Ciencias, pp. 169-189, 1994.
1989
Larrañaga, P., "Clasificación de las provincias españolas frente a los delitos comunes", Criminología y Derecho Penal al Servicio de la Persona. Libro Homenaje al Profesor Antonio Beristain, pp. 289–291, 1989.
1988
Emparanza, J. I., L. Aldámiz-Echevarria, E. G. Pérez-Yarza, P. Larrañaga, J. L. Jimenez, M. Labiano, and I. Ozcoidi, "Prognostic score in acute meningococcemia", Critical Care Medicine, vol. 16, no. 2, pp. 168-169, 1988.
Erquicia, M., and P. Larrañaga, "Clasificación de los alimentos utilizando metodología estadística", Problemas de la Nutrición en las Sociedades Desarrolladas, pp. 270–275, 1988.