Books

Bielza, C., & Larrañaga, P. (2021). “Data-Driven Computational Neuroscience. Machine Learning and Statistical Models“. Cambridge University Press.
Larrañaga, P., Atienza, D., Díaz-Rozo, J., Ogbechie, A., Puerto-Santana, C., & Bielza, C. (2019). “Industrial Applications of Machine Learning“. CRC Press.
Bielza, C., Salmerón, A., Alonso-Betanzos, A., Hidalgo, J. I., Martínez, L., Troncoso, A., Corchado, E., & Corchado, J. M. (2013). “Advances in Artificial Intelligence, Lecture Notes in Artificial Intelligence, Vol. 8109“. Springer.
Bielza, C., Salmerón, A. (2013). “Proceedings of the XV Conference of the Spanish Association for Artificial Intelligence (CAEPIA 2013)”. CEDI.
Pedro Larrañaga, Jose A Lozano. Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation: 2 (Genetic Algorithms and Evolutionary Computation) October 30^th, 2012. Springer.
Ibañez, A., Bielza, C., & Larrañaga, P. (2011). “Scientific Productivity and Visibility of Public Spanish Universities Academic Staff in the Area of Computer Sciences“. Fundación General de la UPM.
Lozano, J. A., Larrañaga, P., Inza, P., & Bengoetxea, E. (2006). “Towards a New Evolutionary Computation. Advances on Estimation of Distribution Algorithms“. Springer.
Ríos-Insua, S., Mateos, A., Bielza, C., & Jimenez, A. (2004). “Operation Research. Deterministic and Stochastic Models“. Centro de Estudios Ramón Areces.
P. Larrañaga, J. A. Lozano, J. M. Peña, I. Inza (2003). Probabilistic Graphical Models for Classification. Ruder Boskovic Institute.
Larrañaga, P., & Lozano, J. A. (2002). “Estimation of Distribution Algorithms. A New Tool for Evolutionary Computation“. Kluwer Academic Publishers.
Ríos-Insua, S., Bielza, C., & Mateos, A. (2002). “Fundamentals of Decision Support Systems“. Ra-Ma, 2002. BibTex
Ballestero, E., Bielza, C., Gómez, M., Maldonado, J. A., & Ballbe, P. (1999). “Health Economy, Statistics for Medical Doctors, Computer-Based Clinical Training“. Dossat 2000.
Aizpurua, J. F., Mendizabal, X., Rodriguez, I., Larrañaga, P., Azkune, I., & Etxeberria, J. (1985). “Matematika. Batxilergo Balioaniztun Bateratua 2“. Elkar.

Book Chapters

C. Puerto-Santana, P. Larrañaga, J. Diaz-Rozo, C. Bielza (2021). An online feature selection methodology for ball-bearing harmonic frequencies based on HMMs. Advances in Intelligent Systems and Computing, 1401, 546-555. Springer
D. Quesada, C. Bielza, P. Larrañaga (2021). Structure learning of high-order dynamic Bayesian networks via particle swarm optimization with order invariant encoding. Lecture Notes in Computer Science, 12886, 158-171. Springer
Córdoba, G. Varando, C. Bielza, P. Larrañaga (2018). A fast Metropolis-Hastings method for generating random correlation matrices. Lecture Notes in Computer Science, 11314, 117-124. Springer
S. Gil-Begue, P. Larrañaga, C. Bielza (2018). Multi-dimensional Bayesian network classifier trees. Lecture Notes in Computer Science, 11314, 354-363. Springer
Córdoba-Sánchez, E.C. Garrido-Merchán, D. Hernández-Lobato, C. Bielza, P. Larrañaga (2018). Bayesian optimization of the PC algorithm for learning Gaussian Bayesian networks. Lecture Notes in Artificial Intelligence, 11160, 44-54. Springer
C. Puerto-Santana, C. Bielza, P. Larrañaga (2018). Asymmetric hidden Markov models with continuous variables. Lecture Notes in Artificial Intelligence, 11160, 98-107. Springer
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. BibTex
Leguey, I., Bielza, C., Larrañaga, P. (2016). Tree-structured Bayesian networks for wrapped Cauchy directional distributions. Lecture Notes in Artificial Intelligence, 9868, 207-216. Springer
Luengo-Sanchez, S., Bielza, C., Larrañaga, P. (2016). Hybrid Gaussian and von Mises model-based clustering. Frontiers in Artificial Intelligence and Applications Series, 285, 855-862. IOS Press
Atienza, D., Bielza, C., Díaz, J., Larrañaga, P. (2016). Anomaly detection with a spatio-temporal tracking of the laser spot. Frontiers in Artificial Intelligence and Applications Series, 284, 137-142, IOS Press
Díaz, J., Bielza, C., Ocaña, J.L., Larrañaga, P. (2016). Development of a cyber-physical system based on selective Gaussian naive Bayes model for a self-predict laser surface heat treatment process control. Machine Leaning for Cyber Physical Systems, 1-8, Springer
Rodríguez-Lujan, L., Bielza, C., Larrañaga, P. (2015). Regularized multivariate von Mises distribution. Lecture Notes in Artificial Intelligence, 9422, 25-35. Springer
Córdoba-Sánchez, I., Bielza, C., Larrañaga, P. (2015). Towards Gaussian Bayesian Network Fusion. Lecture Notes in Artificial Intelligence, 9161, 519-528. Springer
Varando, G., Bielza, C., Larrañaga, P. (2014). Expressive power of binary relevance and chain classifiers based on Bayesian networks for multi-label classification. Lecture Notes in Artificial Intelligence, 8754, 519-534. Springer
Bielza, C., Larrañaga, P. (2014). 28 entries in the Concise Encyclopaedia of Bioinformatics and Computational Biology (second edition), J. Hancock and M.J. Zvelebil (eds.). Wiley
Mihaljevic, B., Larrañaga, P., Bielza, C. (2013). Augmented semi-naive bayes classifier. Advances in Artificial Intelligence, Lecture Notes in Artificial Intelligence, 8109, 159-167. Springer
López-Cruz, P.L., Nielsen, T.D., Bielza, C., Larrañaga, P. (2013). Learning mixtures of polynomials of conditional densities from data. Advances in Artificial Intelligence, Lecture Notes in Artificial Intelligence, 8109, 363-372. Springer
López-Cruz, P.L., Bielza, C., Larrañaga, P. (2013). Learning conditional linear Gaussian classifiers with probabilistic class labels. Advances in Artificial Intelligence, Lecture Notes in Artificial Intelligence, 8109, 139-148. Springer
Guerra, L., Benavides-Piccione, R., Bielza, C., Robles, V., DeFelipe, J., Larrañaga, P. (2013). Semisupervised projected clustering for classifying GABAergic interneurons. Lecture Notes in Artificial Intelligence, 7885, 156-165. Springer
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. BibTex
P. Larrañaga (2012). 1969-1980: Mondrag_on-Toulouse-Mondrag_on-Berkeley-Mondrag_on. Festschrift in Honour of Ramon López de Mántaras, 205-216, Artificial Intelligence Research Institute
Santana, R., Bielza, C., Larrañaga, P. (2010). Synergies between network-based representation and probabilistic graphical models for classification, inference and optimization problems in neuroscience. Lecture Notes in Artificial Intelligence, 6098, 149-158. Springer
Borchani, H., Larrañaga, P., Bielza, C. (2010). Mining concept-drifting data streams containing labeled and unlabeled instances. Lecture Notes in Artificial Intelligence, 6096, 531-540. Springer
Santana, R., Bielza, C., Larrañaga, P. (2010). Using probabilistic dependencies improves the search of conductance-based compartmental neuron models. Lecture Notes in Computer Science, 6023, 170-181. Springer
Díaz, E., Ponce-de-León, E., Larrañaga, P., Bielza, C. (2009). Probabilistic graphical Markov model learning: An adaptive strategy. Lecture Notes in Artificial Intelligence, 5845, 225-236. Springer
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. BibTex
D. Morales, E. Bengoetxea, P. Larrañaga (2009). Combining multi-classifiers with Gaussian-stacking multiclassifiers for human embryo selection. Data Mining and Medical Knowledge Management: Cases and Applications, 307-331, IGI Global
Echegoyen, R. Santana, J. A. Lozano, P. Larrañaga (2008). The impact of exact probabilistic learning algorithms in EDAs based on Bayesian network. Linkage in Evolutionary Computation, 109-139, Springer
López, M., Bielza, C., Sarro, L.M. (2006). Bayesian classifiers for variable stars. Astronomical Data Analysis Software and Systems XV, 351, 161-164. Astronomical Society of the Pacific Conference Series
Robles, J. M. Peña, P. Larrañaga, M. S. Pérez, V. Herves (2006). GA-EDA: A new hybrid cooperative search evolutionary algorithm. Towards a New Evolutionary Computation. Advances on Estimation of Distribution Algorithms, 187-220, Springer
T. Miquélez, E. Bengoetxea, P. Larrañaga (2006). Bayesian classifiers in optimization: An EDAlike approach. Towards a New Evolutionary Computation. Advances on Estimation of Distribution Algorithms, 221-242, Springer
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. BibTex
S. Dizdarevich, P. Larrañaga, B. Sierra, J. A. Lozano, J. M. Peña (2005). Combining statistical and machine learning based classifiers in the prediction of corporate failure. Artificial Intelligence in Accounting and Auditing. Volume 6. International Perspective, 177-211, Markus Wiener Publishers
P. Larrañaga, I. Inza, J. L. Flores (2005). A guide to the literature on inferring genetic networks by probabilistic graphical models. Data Analysis and Visualization in Genomics and Proteomics, 215-238, John Wiley.
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. BibTex
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. BibTex
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. BibTex
30. Bielza, C., Fernández del Pozo, J.A., Lucas, P. (2004). Optimal decision explanation by extracting regularity patterns. Research and Development in Intelligent Systems XX, 283-294. Springer
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. BibTex
Bielza, C., and S. Ríos-Insua, “Análisis de Decisiones Clínicas”, Manual de Informática Médica: Menarini – Caduceo Multimedia, pp. 467-491, 2003. BibTex
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. BibTex
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.
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.
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.
I. Inza, P. Larrañaga, B. Sierra (2002). Estimation of distribution algorithms for feature subset selection in large dimensionality domains. Data Mining: A euristic Approach, 97-116, Idea Group Publishing.
C. Cotta, E. Alba, R. Sagarna, P. Larrañaga (2002). Adjusting weights in Artificial neural networks using evolutionary algorithms. Estimation of Distribution Algorithms. A New Tool for Evolutionary Computation, 361-377, Kluwer Academic Publishers.
J. Roure, P. Larrañaga, R. Sangüesa (2002). An empirical comparison between K-means, GAs and EDAs in partitional clustering. Estimation of Distribution Algorithms. A New Tool for Evolutionary Computation, 343-360, Kluwer Academic Publishers.
L.M. de Campos, J. A. Gámez, P. Larrañaga, S. Moral, T. Romero (2002). Partial abductive inference in Bayesian networks: An empirical comparison between GAs and EDAs. Estimation of Distribution Algorithms. A New Tool for Evolutionary Computation, 323-341, Kluwer Academic Publishers.
B. Sierra, E. A. Jiménez, I. Inza, P. Larrañaga, J. Muruzábal (2002). Rule induction by estimation of distribution algorithms. Estimation of Distribution Algorithms. A New Tool for Evolutionary Computation, 313-322, Kluwer Academic Publishers.
I. Inza, P. Larrañaga, B. Sierra (2002). Feature weighting for nearest neighbor by estimation of distribution algorithms. Estimation of Distribution Algorithms. A New Tool for Evolutionary Computation, 295-311, Kluwer Academic Publishers.
I. Inza, P. Larrañaga, B. Sierra (2002). Feature subset selection by estimation of distribution algorithms. Estimation of Distribution Algorithms. A New Tool for Evolutionary Computation, 269-293, Kluwer Academic Publishers.
E. Bengoetxea, P. Larrañaga, I. Bloch, A. Perchant (2002). Solving graph matching with EDAs using a permutation-based representation. Estimation of Distribution Algorithms. A New Tool for Evolutionary Computation, 243-265, Kluwer Academic Publishers.
V. Robles, P. de Miguel, P. Larrañaga (2002). Solving the traveling salesman problem with EDAs. Estimation of Distribution Algorithms. A New Tool for Evolutionary Computation, 211-229, Kluwer Academic Publishers.
R. Sagarna, P. Larrañaga (2002). Solving the 0-1 knapsack problem with EDAs. Estimation of Distribution Algorithms. A New Tool for Evolutionary Computation, 195-209, Kluwer Academic Publishers.
E. Bengoetxea, T. Miquélez, P. Larrañaga, J. A. Lozano (2002). Experimental results in function optimization with EDAs in continuous domains. Estimation of Distribution Algorithms. A New Tool for Evolutionary Computation, 181-194, Kluwer Academic Publishers.
C. González, J. A. Lozano, P. Larrañaga (2002). Mathematical modeling of discrete estimation of distribution algorithms. Estimation of Distribution Algorithms. A New Tool for Evolutionary Computation, 147-163, Kluwer Academic Publishers.
J. A. Lozano, R. Sagarna, P. Larrañaga (2002). Parallel estimation of distribution algorithms. Estimation of Distribution Algorithms. A New Tool for Evolutionary Computation, 129-145, Kluwer Academic Publishers.
J. M. Peña, J. A. Lozano, P. Larrañaga (2002). Benefits of data clustering in multimodal function optimization via EDAs. Estimation of Distribution Algorithms. A New Tool for Evolutionary Computation, 101-127, Kluwer Academic Publishers.
P. Larrañaga (2002). A review on estimation of distribution algorithms. Estimation of Distribution Algorithms. A New Tool for Evolutionary Computation, 57-100, Kluwer Academic Publishers.
P. Larrañaga (2002). An introduction to probabilistic graphical models. Estimation of Distribution Algorithms. A New Tool for Evolutionary Computation, 27-56, Kluwer Academic Publishers.
Fernández del Pozo, J.A., Bielza, C. (2002). An interactive framework for open queries in decision support systems. Lecture Notes in Artificial Intelligence, 2527, 254-264. Springer.
Martín, J., Bielza, C. (2001). Aplicación de técnicas de simulación al análisis de decisiones: Estudio de una línea de clasificación de frutas. Gestao da Tecnología Empresarial e da Informacao: Conceitos e Estudos de Casos, 181-194. Editora Internet
Ríos-Insua, S., Gómez, M., Bielza, C., Fernández del Pozo, J.A. (2000). Implementation of IctNeo: a decision support system for jaundice management. Operations Research Proceedings 1999, Gesellschaft fur Operations Research e.V., 554-559. Springer
Bielza, C., Ríos-Insua, S., Gómez, M., Fernández del Pozo, J.A. (2000). Sensitivity analysis in IctNeo. Robust Bayesian Analysis, Lecture Notes in Statistics, 152, 317-334. Springer.
Gómez, M., Ríos-Insua, S., Bielza, C., Fernández del Pozo, J.A. (2000). Multiattribute utility analysis in the IctNeo system. Research and Practice in Multiple Criteria Decision Making, Lecture Notes in Economics and Mathematical Systems, 487, 81-92. Springer
P. Larrañaga, C. M. H. Kuijpers (1999). Moral graph (triangulation of). Encyclopedia of Statistical Sciences. Update Volume 3, 462-464, John Wiley & Sons Ltd.
Ríos-Insua, S., Bielza, C., Gómez, M., Fernández del Pozo, J.A., Sánchez Luna, M., Caballero, S. (1998). An intelligent decision system for jaundice management in newborn babies. Applied Decision Analysis, 133-144. Kluwer.
Bielza, C., Ríos Insua, D. (1998). Modelos gráficos para la toma de decisiones. Sistemas Expertos Probabilísticos, Colección Ciencia y Técnica, 20, 163-185. Eds. de la Universidad de Castilla – La Mancha
Ríos Insua, D., Bielza, C., Martín, J., Salewicz, K.A. (1998). Intelligent decision support for reservoir operations. Applied Decision Analysis, 63-72. Kluwer.
Ríos Insua, D., Bielza, C., Martín, J., Salewicz, K. (1997). BayRes: a system for stochastic multiobjective reservoir operations. Advances in Multiple Objective and Goal Programming, Lecture Notes in Economics and Mathematical Systems, 455, 319-327. Springer.
Ríos Insua, D., Salewicz, K.A.,Müller, P., Bielza, C. (1997). Bayesian methods in reservoir operations: The Zambezi river case. The Practice of Bayesian Analysis, 107-130. Arnold
Bielza, C., Ríos Insua, D., Ríos-Insua, S. (1996). Inuence diagrams under partial information. Bayesian Statistics 5, 491-497. Oxford U.P.
P. Larrañaga, C. M. H. Kuijpers, R. H. Murga, Y. Yurramendi, M. Graña, J. A. Lozano, X. Albizuri, A. d’Anjou, F. J. Torrealdea (1996). Genetic algorithms applied to Bayesian networks. Computational Learning and Probabilistic Reasoning, 211-234, John Wiley & Sons Ltd.
Ríos-Insua, S., Mateos, A., Bielza, C. (1994). Teoría de la utilidad e inteligencia Artificial. Fronteras de la Informática, 169-189. Real Academia de Ciencias.
P. Larrañaga (1989). 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, 289-292, IVAC-KREI.