Pedro Larrañaga

296 papers A* 1A 8B 12C 8Misc 6Journal 179Unranked 52

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Bandwidth selectors on semiparametric Bayesian networks. Inf. Sci. Victor Alejandre, Concha Bielza, Pedro Larrañaga
2026	—	`ed.`	Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2025, Porto, Portugal, September 15-19, 2025, Proceedings, Part I ECML/PKDD (1) Rita P. Ribeiro, Bernhard Pfahringer, Nathalie Japkowicz, Pedro Larrañaga, Alípio M. Jorge, Carlos Soares, Pedro H. Abreu, João Gama
2026	—	`ed.`	Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2025, Porto, Portugal, September 15-19, 2025, Proceedings, Part II ECML/PKDD (2) Rita P. Ribeiro, Bernhard Pfahringer, Nathalie Japkowicz, Pedro Larrañaga, Alípio M. Jorge, Carlos Soares, Pedro H. Abreu, João Gama
2026	—	`ed.`	Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2025, Porto, Portugal, September 15-19, 2025, Proceedings, Part III ECML/PKDD (3) Rita P. Ribeiro, Bernhard Pfahringer, Nathalie Japkowicz, Pedro Larrañaga, Alípio M. Jorge, Carlos Soares, Pedro H. Abreu, João Gama
2026	—	`ed.`	Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2025, Porto, Portugal, September 15-19, 2025, Proceedings, Part IV ECML/PKDD (4) Rita P. Ribeiro, Bernhard Pfahringer, Nathalie Japkowicz, Pedro Larrañaga, Alípio M. Jorge, Carlos Soares, Pedro H. Abreu, João Gama
2026	—	`ed.`	Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2025, Porto, Portugal, September 15-19, 2025, Proceedings, Part V ECML/PKDD (5) Rita P. Ribeiro, Bernhard Pfahringer, Nathalie Japkowicz, Pedro Larrañaga, Alípio M. Jorge, Carlos Soares, Pedro H. Abreu, João Gama
2026	—	`ed.`	Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2025, Porto, Portugal, September 15-19, 2025, Proceedings, Part VI ECML/PKDD (6) Rita P. Ribeiro, Bernhard Pfahringer, Nathalie Japkowicz, Pedro Larrañaga, Alípio M. Jorge, Carlos Soares, Pedro H. Abreu, João Gama
2026	—	`ed.`	Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2025, Porto, Portugal, September 15-19, 2025, Proceedings, Part VII ECML/PKDD (7) Rita P. Ribeiro, Bernhard Pfahringer, Nathalie Japkowicz, Pedro Larrañaga, Alípio M. Jorge, Carlos Soares, Pedro H. Abreu, João Gama
2026	—	`ed.`	Machine Learning and Knowledge Discovery in Databases. Research Track and Applied Data Science Track - European Conference, ECML PKDD 2025, Porto, Portugal, September 15-19, 2025, Proceedings, Part VIII ECML/PKDD (8) Bernhard Pfahringer, Nathalie Japkowicz, Pedro Larrañaga, Rita P. Ribeiro, Inês Dutra, Mykola Pechenizkiy, Paulo Cortez, Sepideh Pashami, Alípio M. Jorge, Carlos Soares, Pedro H. Abreu, João Gama
2026	J	`jnl`	Optimal Transport Group Counterfactual Explanations. CoRR Enrique Valero-Leal, Bernd Bischl, Pedro Larrañaga, Concha Bielza, Giuseppe Casalicchio
2025	J	`jnl`	Actionable Counterfactual Explanations Using Bayesian Networks and Path Planning with Applications to Environmental Quality Improvement. CoRR Enrique Valero-Leal, Pedro Larrañaga, Concha Bielza
2025	J	`jnl`	Bandwidth Selectors on Semiparametric Bayesian Networks. CoRR Victor Alejandre, Concha Bielza, Pedro Larrañaga
2025	J	`jnl`	Binned semiparametric Bayesian networks. CoRR Rafael Sojo, Javier Diaz-Rozo, Concha Bielza, Pedro Larrañaga
2025	J	`jnl`	Discovering Genetic Variants in Hypertrophic Cardiomyopathy With Multiple Machine Learning Techniques. IEEE Trans. Comput. Biol. Bioinform. Dafne Lozano-Paredes, Luis Bote-Curiel, María Sabater-Molina, Concha Bielza, Juan-Ramón Gimeno-Blanes, Sergio Muñoz-Romero, Francisco Javier Gimeno-Blanes, Pedro Larrañaga, José Luis Rojo-Álvarez
2025	J	`jnl`	dbnR : Gaussian Dynamic Bayesian Network Learning and Inference in J. Stat. Softw. David Quesada, Pedro Larrañaga, Concha Bielza
2024	J	`jnl`	BN-BacArena: Bayesian network extension of BacArena for the dynamic simulation of microbial communities. Bioinform. Telmo Blasco, Francesco Balzerani, Luis Vitores Valcarcel, Pedro Larrañaga, Concha Bielza, María Pilar Francino, José Ángel Rufián-Henares, Francisco J. Planes, Sergio Pérez-Burillo
2024	J	`jnl`	EDAspy: An extensible python package for estimation of distribution algorithms. Neurocomputing Vicente P. Soloviev, Pedro Larrañaga, Concha Bielza
2024	J	`jnl`	Estimation of Distribution Algorithms in Machine Learning: A Survey. IEEE Trans. Evol. Comput. Pedro Larrañaga, Concha Bielza
2024	J	`jnl`	Feature Saliencies in Asymmetric Hidden Markov Models. IEEE Trans. Neural Networks Learn. Syst. Carlos Puerto-Santana, Pedro Larrañaga, Concha Bielza
2024	—	`conf`	Multi-objective Counterfactuals in Bayesian Classifiers with Estimation of Distribution Algorithms. PGM Daniel Zaragoza-Pellicer, Concha Bielza, Pedro Larrañaga
2024	J	`jnl`	Semiparametric Estimation of Distribution Algorithms for Continuous Optimization. IEEE Trans. Evol. Comput. Vicente P. Soloviev, Concha Bielza, Pedro Larrañaga
2023	Misc	`conf`	Anomaly-Based Intrusion Detection in IIoT Networks Using Transformer Models. CSR Jorge Casajús-Setién, Concha Bielza, Pedro Larrañaga
2023	J	`jnl`	Causal reinforcement learning based on Bayesian networks applied to industrial settings. Eng. Appl. Artif. Intell. Gabriel Valverde, David Quesada, Pedro Larrañaga, Concha Bielza
2023	J	`jnl`	Classifying the evolution of COVID-19 severity on patients with combined dynamic Bayesian networks and neural networks. CoRR David Quesada, Pedro Larrañaga, Concha Bielza
2023	J	`jnl`	Constraint-based and hybrid structure learning of multidimensional continuous-time Bayesian network classifiers. Int. J. Approx. Reason. Carlos Villa-Blanco, Alessandro Bregoli, Concha Bielza, Pedro Larrañaga, Fabio Stella
2023	J	`jnl`	Context-specific kernel-based hidden Markov model for time series analysis. CoRR Carlos Puerto-Santana, Concha Bielza, Pedro Larrañaga, Gustav Eje Henter
2023	J	`jnl`	Efficient search for relevance explanations using MAP-independence in Bayesian networks. Int. J. Approx. Reason. Enrique Valero-Leal, Concha Bielza, Pedro Larrañaga, Silja Renooij
2023	J	`jnl`	Feature subset selection for data and feature streams: a review. Artif. Intell. Rev. Carlos Villa-Blanco, Concha Bielza, Pedro Larrañaga
2023	J	`jnl`	Feature subset selection in data-stream environments using asymmetric hidden Markov models and novelty detection. Neurocomputing Carlos Puerto-Santana, Pedro Larrañaga, Concha Bielza
2023	—	`conf`	High-Dimensional Feature Characterization of Single Nucleotide Variants in Hypertrophic Cardiomyopathy. CinC Dafne Lozano-Paredes, Luis Bote, Concha Bielza, Pedro Larrañaga, María Sabater-Molina, Juan Ramón Gimeno, Sergio Muñoz, Francisco Javier Gimeno-Blanes, José Luis Rojo-Álvarez
2023	J	`jnl`	Learning massive interpretable gene regulatory networks of the human brain by merging Bayesian networks. PLoS Comput. Biol. Nikolas Bernaola, Mario Michiels, Pedro Larrañaga, Concha Bielza
2023	J	`jnl`	Quantum approximate optimization algorithm for Bayesian network structure learning. Quantum Inf. Process. Vicente P. Soloviev, Concha Bielza, Pedro Larrañaga
2023	B	`conf`	Variational Quantum Algorithm Parameter Tuning with Estimation of Distribution Algorithms. CEC Vicente P. Soloviev, Pedro Larrañaga, Concha Bielza
2022	J	`jnl`	Asymmetric HMMs for Online Ball-Bearing Health Assessments. IEEE Internet Things J. Carlos Puerto-Santana, Concha Bielza, Javier Diaz-Rozo, Guillem Ramirez-Gargallo, Filippo Mantovani, Gaizka Virumbrales, Jesús Labarta, Pedro Larrañaga
2022	J	`jnl`	Autoregressive Asymmetric Linear Gaussian Hidden Markov Models. IEEE Trans. Pattern Anal. Mach. Intell. Carlos Puerto-Santana, Pedro Larrañaga, Concha Bielza
2022	J	`jnl`	Estimation of distribution algorithms using Gaussian Bayesian networks to solve industrial optimization problems constrained by environment variables. J. Comb. Optim. Vicente P. Soloviev, Pedro Larrañaga, Concha Bielza
2022	—	`conf`	Evolutive Adversarially-Trained Bayesian Network Autoencoder for Interpretable Anomaly Detection. PGM Jorge Casajús-Setién, Concha Bielza, Pedro Larrañaga
2022	—	`conf`	Interpreting Time-Varying Dynamic Bayesian Networks for Earth Climate Modelling. PGM Enrique Valero-Leal, Pedro Larrañaga, Concha Bielza
2022	J	`jnl`	Multipartition clustering of mixed data with Bayesian networks. Int. J. Intell. Syst. Fernando Rodriguez-Sanchez, Concha Bielza, Pedro Larrañaga
2022	J	`jnl`	Piecewise forecasting of nonlinear time series with model tree dynamic Bayesian networks. Int. J. Intell. Syst. David Quesada, Concha Bielza, Pedro Fontán, Pedro Larrañaga
2022	J	`jnl`	PyBNesian: An extensible python package for Bayesian networks. Neurocomputing David Atienza, Concha Bielza, Pedro Larrañaga
2022	J	`jnl`	Quantum Approximate Optimization Algorithm for Bayesian network structure learning. CoRR Vicente P. Soloviev, Concha Bielza, Pedro Larrañaga
2022	—	`conf`	Quantum parametric circuit optimization with estimation of distribution algorithms. GECCO Companion Vicente P. Soloviev, Pedro Larrañaga, Concha Bielza
2022	J	`jnl`	Semiparametric Bayesian networks. Inf. Sci. David Atienza, Concha Bielza, Pedro Larrañaga
2022	—	`conf`	Structure learning algorithms for multidimensional continuous-time Bayesian network classifiers. PGM Carlos Villa-Blanco, Alessandro Bregoli, Concha Bielza, Pedro Larrañaga, Fabio Stella
2021	—	`conf`	An Online Feature Selection Methodology for Ball-Bearing Harmonic Frequencies Based on HMMs. SOCO Carlos Puerto-Santana, Pedro Larrañaga, Javier Diaz-Rozo, Concha Bielza
2021	J	`jnl`	BayeSuites: An open web framework for massive Bayesian networks focused on neuroscience. Neurocomputing Mario Michiels, Pedro Larrañaga, Concha Bielza
2021	J	`jnl`	Bayesian networks for interpretable machine learning and optimization. Neurocomputing Bojan Mihaljevic, Concha Bielza, Pedro Larrañaga
2021	J	`jnl`	Comparing the Electrophysiology and Morphology of Human and Mouse Layer 2/3 Pyramidal Neurons With Bayesian Networks. Frontiers Neuroinformatics Bojan Mihaljevic, Pedro Larrañaga, Concha Bielza
2021	J	`jnl`	Long-term forecasting of multivariate time series in industrial furnaces with dynamic Gaussian Bayesian networks. Eng. Appl. Artif. Intell. David Quesada, Gabriel Valverde, Pedro Larrañaga, Concha Bielza
2021	J	`jnl`	Multi-dimensional Bayesian network classifiers: A survey. Artif. Intell. Rev. Santiago Gil-Begue, Concha Bielza, Pedro Larrañaga
2021	J	`jnl`	Multidimensional continuous time Bayesian network classifiers. Int. J. Intell. Syst. Carlos Villa-Blanco, Pedro Larrañaga, Concha Bielza
2021	B	`conf`	Quantum-Inspired Estimation Of Distribution Algorithm To Solve The Travelling Salesman Problem. CEC Vicente P. Soloviev, Concha Bielza, Pedro Larrañaga
2021	J	`jnl`	Semiparametric Bayesian Networks. CoRR David Atienza, Concha Bielza, Pedro Larrañaga
2021	Misc	`conf`	Structure Learning of High-Order Dynamic Bayesian Networks via Particle Swarm Optimization with Order Invariant Encoding. HAIS David Quesada, Concha Bielza, Pedro Larrañaga
2020	J	`jnl`	Autoregressive Asymmetric Linear Gaussian Hidden Markov Models. CoRR Carlos Puerto-Santana, Pedro Larrañaga, Concha Bielza
2020	—	`conf`	BayesSuites: An Open Web Framework for Visualization of Massive Bayesian Networks. PGM Nikolas Bernaola, Mario Michiels, Concha Bielza, Pedro Larrañaga
2020	J	`jnl`	Incremental Learning of Latent Forests. IEEE Access Fernando Rodriguez-Sanchez, Pedro Larrañaga, Concha Bielza
2020	J	`jnl`	Machine-tool condition monitoring with Gaussian mixture models-based dynamic probabilistic clustering. Eng. Appl. Artif. Intell. Javier Diaz-Rozo, Concha Bielza, Pedro Larrañaga
2020	J	`jnl`	On generating random Gaussian graphical models. Int. J. Approx. Reason. Irene Córdoba, Gherardo Varando, Concha Bielza, Pedro Larrañaga
2020	J	`jnl`	Sparse Cholesky Covariance Parametrization for Recovering Latent Structure in Ordered Data. IEEE Access Irene Córdoba, Concha Bielza, Pedro Larrañaga, Gherardo Varando
2020	J	`jnl`	Sparse Cholesky covariance parametrization for recovering latent structure in ordered data. CoRR Irene Córdoba, Concha Bielza, Pedro Larrañaga, Gherardo Varando
2019	J	`jnl`	A Directional-Linear Bayesian Network and Its Application for Clustering and Simulation of Neural Somas. IEEE Access Sergio Luengo-Sanchez, Pedro Larrañaga, Concha Bielza
2019	J	`jnl`	A circular-linear dependence measure under Johnson-Wehrly distributions and its application in Bayesian networks. Inf. Sci. Ignacio Leguey, Pedro Larrañaga, Concha Bielza, Shogo Kato
2019	J	`jnl`	Circular Bayesian classifiers using wrapped Cauchy distributions. Data Knowl. Eng. Ignacio Leguey, Concha Bielza, Pedro Larrañaga
2019	J	`jnl`	Learning tractable Bayesian networks in the space of elimination orders. Artif. Intell. Marco Benjumeda, Concha Bielza, Pedro Larrañaga
2019	J	`jnl`	Random Forests for Regression as a Weighted Sum of ${k}$ -Potential Nearest Neighbors. IEEE Access Pablo Fernandez-Gonzalez, Concepcion Bielza, Pedro Larrañaga
2019	J	`jnl`	Tractable learning of Bayesian networks from partially observed data. Pattern Recognit. Marco Benjumeda, Sergio Luengo-Sanchez, Pedro Larrañaga, Concha Bielza
2018	J	`jnl`	3D morphology-based clustering and simulation of human pyramidal cell dendritic spines. PLoS Comput. Biol. Sergio Luengo-Sanchez, Isabel Fernaud, Concha Bielza, Ruth Benavides-Piccione, Pedro Larrañaga, Javier DeFelipe
2018	—	`conf`	A Fast Metropolis-Hastings Method for Generating Random Correlation Matrices. IDEAL (1) Irene Córdoba, Gherardo Varando, Concha Bielza, Pedro Larrañaga
2018	—	`conf`	A partial orthogonalization method for simulating covariance and concentration graph matrices. PGM Irene Córdoba, Gherardo Varando, Concha Bielza, Pedro Larrañaga
2018	J	`jnl`	A regularity index for dendrites - local statistics of a neuron's input space. PLoS Comput. Biol. Laura Anton-Sanchez, Felix Effenberger, Concha Bielza, Pedro Larrañaga, Hermann Cuntz
2018	—	`conf`	Asymmetric Hidden Markov Models with Continuous Variables. CAEPIA Carlos Puerto-Santana, Concha Bielza, Pedro Larrañaga
2018	—	`conf`	Bayesian Optimization of the PC Algorithm for Learning Gaussian Bayesian Networks. CAEPIA Irene Córdoba, Eduardo C. Garrido-Merchán, Daniel Hernández-Lobato, Concha Bielza, Pedro Larrañaga
2018	J	`jnl`	Bayesian optimization of the PC algorithm for learning Gaussian Bayesian networks. CoRR Irene Córdoba-Sánchez, Eduardo C. Garrido-Merchán, Daniel Hernández-Lobato, Concha Bielza, Pedro Larrañaga
2018	J	`jnl`	Clustering of Data Streams With Dynamic Gaussian Mixture Models: An IoT Application in Industrial Processes. IEEE Internet Things J. Javier Diaz-Rozo, Concha Bielza, Pedro Larrañaga
2018	—	`conf`	Discrete model-based clustering with overlapping subsets of attributes. PGM Fernando Rodriguez-Sanchez, Pedro Larrañaga, Concha Bielza
2018	—	`conf`	Learning Bayesian network classifiers with completed partially directed acyclic graphs. PGM Bojan Mihaljevic, Concha Bielza, Pedro Larrañaga
2018	J	`jnl`	Markov Property in Generative Classifiers. CoRR Gherardo Varando, Concha Bielza, Pedro Larrañaga, Eva Riccomagno
2018	—	`conf`	Multi-dimensional Bayesian Network Classifier Trees. IDEAL (1) Santiago Gil-Begue, Pedro Larrañaga, Concha Bielza
2018	J	`jnl`	Towards Gaussian Bayesian Network Fusion. CoRR Irene Córdoba, Concha Bielza, Pedro Larrañaga
2018	J	`jnl`	Towards a supervised classification of neocortical interneuron morphologies. BMC Bioinform. Bojan Mihaljevic, Pedro Larrañaga, Ruth Benavides-Piccione, Sean L. Hill, Javier DeFelipe, Concha Bielza
2018	J	`jnl`	Tractability of most probable explanations in multidimensional Bayesian network classifiers. Int. J. Approx. Reason. Marco Benjumeda, Concha Bielza, Pedro Larrañaga
2018	J	`jnl`	bnclassify: Learning Bayesian Network Classifiers. R J. Bojan Mihaljevic, Concha Bielza, Pedro Larrañaga
2017	C	`conf`	Architecture for anomaly detection in a laser heating surface process. ETFA Javier Mesonero, Concha Bielza, Pedro Larrañaga
2017	J	`jnl`	Frobenius Norm Regularization for the Multivariate Von Mises Distribution. Int. J. Intell. Syst. Luis Rodriguez-Lujan, Pedro Larrañaga, Concha Bielza
2017	J	`jnl`	Network design through forests with degree- and role-constrained minimum spanning trees. J. Heuristics Laura Anton-Sanchez, Concha Bielza, Pedro Larrañaga
2017	J	`jnl`	Univariate and bivariate truncated von Mises distributions. Prog. Artif. Intell. Pablo Fernandez-Gonzalez, Concha Bielza, Pedro Larrañaga
2016	J	`jnl`	A review of undirected and acyclic directed Gaussian Markov model selection and estimation. CoRR Irene Córdoba-Sánchez, Concha Bielza, Pedro Larrañaga
2016	—	`conf`	Anomaly Detection with a Spatio-Temporal Tracking of the Laser Spot. STAIRS David Atienza, Concha Bielza, Javier Díaz, Pedro Larrañaga
2016	J	`jnl`	Decision functions for chain classifiers based on Bayesian networks for multi-label classification. Int. J. Approx. Reason. Gherardo Varando, Concha Bielza, Pedro Larrañaga
2016	J	`jnl`	Dendritic and Axonal Wiring Optimization of Cortical GABAergic Interneurons. Neuroinformatics Laura Anton-Sanchez, Concha Bielza, Ruth Benavides-Piccione, Javier DeFelipe, Pedro Larrañaga
2016	—	`conf`	Dynamic Bayesian Network-Based Anomaly Detection for In-Process Visual Inspection of Laser Surface Heat Treatment. ML4CPS Alberto Ogbechie, Javier Diaz-Rozo, Pedro Larrañaga, Concha Bielza
2016	J	`jnl`	Genetic algorithms and Gaussian Bayesian networks to uncover the predictive core set of bibliometric indices. J. Assoc. Inf. Sci. Technol. Alfonso Ibáñez, Rubén Armañanzas, Concha Bielza, Pedro Larrañaga
2016	A	`conf`	Hybrid Gaussian and von Mises Model-Based Clustering. ECAI Sergio Luengo-Sanchez, Concha Bielza, Pedro Larrañaga
2016	J	`jnl`	Learning Bayesian networks with low inference complexity. Prog. Artif. Intell. Marco Benjumeda, Pedro Larrañaga, Concha Bielza
2016	—	`conf`	Learning Tractable Multidimensional Bayesian Network Classifiers. Probabilistic Graphical Models Marco Benjumeda, Concha Bielza, Pedro Larrañaga
2016	J	`jnl`	Mining multi-dimensional concept-drifting data streams using Bayesian network classifiers. Intell. Data Anal. Hanen Borchani, Pedro Larrañaga, João Gama, Concha Bielza
2016	—	`conf`	Tree-Structured Bayesian Networks for Wrapped Cauchy Directional Distributions. CAEPIA Ignacio Leguey, Concha Bielza, Pedro Larrañaga
2015	J	`jnl`	A survey on multi-output regression. WIREs Data Mining Knowl. Discov. Hanen Borchani, Gherardo Varando, Concha Bielza, Pedro Larrañaga
2015	J	`jnl`	Bayesian Network Classifiers for Categorizing Cortical GABAergic Interneurons. Neuroinformatics Bojan Mihaljevic, Ruth Benavides-Piccione, Concha Bielza, Javier DeFelipe, Pedro Larrañaga
2015	J	`jnl`	Classifying GABAergic interneurons with semi-supervised projected model-based clustering. Artif. Intell. Medicine Bojan Mihaljevic, Ruth Benavides-Piccione, Luis Guerra, Javier DeFelipe, Pedro Larrañaga, Concha Bielza
2015	J	`jnl`	Conditional Density Approximations with Mixtures of Polynomials. Int. J. Intell. Syst. Gherardo Varando, Pedro L. López-Cruz, Thomas D. Nielsen, Pedro Larrañaga, Concha Bielza
2015	J	`jnl`	Decision boundary for discrete Bayesian network classifiers. J. Mach. Learn. Res. Gherardo Varando, Concha Bielza, Pedro Larrañaga
2015	—	`conf`	Development of a Cyber-Physical System based on selective Gaussian naïve Bayes model for a self-predict laser surface heat treatment process control. ML4CPS Javier Díaz, Concha Bielza, Jose L. Ocaña, Pedro Larrañaga
2015	J	`jnl`	Directional naive Bayes classifiers. Pattern Anal. Appl. Pedro L. López-Cruz, Concha Bielza, Pedro Larrañaga
2015	J	`jnl`	Interval-based ranking in noisy evolutionary multi-objective optimization. Comput. Optim. Appl. Hossein Karshenas, Concha Bielza, Pedro Larrañaga
2015	—	`conf`	Regularized Multivariate von Mises Distribution. CAEPIA Luis Rodriguez-Lujan, Concha Bielza, Pedro Larrañaga
2015	C	`conf`	Towards Gaussian Bayesian Network Fusion. ECSQARU Irene Córdoba-Sánchez, Concha Bielza, Pedro Larrañaga
2014	J	`jnl`	Bayesian network modeling of the consensus between experts: An application to neuron classification. Int. J. Approx. Reason. Pedro L. López-Cruz, Pedro Larrañaga, Javier DeFelipe, Concha Bielza
2014	J	`jnl`	Bayesian networks in neuroscience: a survey. Frontiers Comput. Neurosci. Concha Bielza, Pedro Larrañaga
2014	J	`jnl`	Cost-sensitive selective naive Bayes classifiers for predicting the increase of the h-index for scientific journals. Neurocomputing Alfonso Ibáñez, Concha Bielza, Pedro Larrañaga
2014	J	`jnl`	Discrete Bayesian Network Classifiers: A Survey. ACM Comput. Surv. Concha Bielza, Pedro Larrañaga
2014	—	`conf`	Expressive Power of Binary Relevance and Chain Classifiers Based on Bayesian Networks for Multi-label Classification. Probabilistic Graphical Models Gherardo Varando, Concha Bielza, Pedro Larrañaga
2014	J	`jnl`	Learning mixtures of polynomials of multidimensional probability densities from data using B-spline interpolation. Int. J. Approx. Reason. Pedro L. López-Cruz, Concha Bielza, Pedro Larrañaga
2014	J	`jnl`	Multi-Dimensional Classification with Super-Classes. IEEE Trans. Knowl. Data Eng. Jesse Read, Concha Bielza, Pedro Larrañaga
2014	J	`jnl`	Multi-dimensional classification of GABAergic interneurons with Bayesian network-modeled label uncertainty. Frontiers Comput. Neurosci. Bojan Mihaljevic, Concha Bielza, Ruth Benavides-Piccione, Javier DeFelipe, Pedro Larrañaga
2014	J	`jnl`	Multi-label classification with Bayesian network-based chain classifiers. Pattern Recognit. Lett. Luis Enrique Sucar, Concha Bielza, Eduardo F. Morales, Pablo Hernandez-Leal, Julio H. Zaragoza, Pedro Larrañaga
2014	J	`jnl`	Multiobjective Estimation of Distribution Algorithm Based on Joint Modeling of Objectives and Variables. IEEE Trans. Evol. Comput. Hossein Karshenas, Roberto Santana, Concha Bielza, Pedro Larrañaga
2014	J	`jnl`	Semi-supervised projected model-based clustering. Data Min. Knowl. Discov. Luis Guerra, Concha Bielza, Víctor Robles, Pedro Larrañaga
2013	J	`jnl`	A new measure for gene expression biclustering based on non-parametric correlation. Comput. Methods Programs Biomed. Jose Luis Flores, Iñaki Inza, Pedro Larrañaga, Borja Calvo
2013	J	`jnl`	A review on evolutionary algorithms in Bayesian network learning and inference tasks. Inf. Sci. Pedro Larrañaga, Hossein Karshenas, Concha Bielza, Roberto Santana
2013	J	`jnl`	An L Int. J. Artif. Intell. Tools Diego Vidaurre, Concha Bielza, Pedro Larrañaga
2013	—	`conf`	Augmented Semi-naive Bayes Classifier. CAEPIA Bojan Mihaljevic, Pedro Larrañaga, Concha Bielza
2013	J	`jnl`	Bayesian Sparse Partial Least Squares. Neural Comput. Diego Vidaurre, Marcel A. J. van Gerven, Concha Bielza, Pedro Larrañaga, Tom Heskes
2013	B	`conf`	Bayesian networks to answer challenging neuroscience questions. CBMS Pedro Larrañaga, Concha Bielza
2013	J	`jnl`	Classification of neural signals from sparse autoregressive features. Neurocomputing Diego Vidaurre, Concha Bielza, Pedro Larrañaga
2013	J	`jnl`	Cluster methods for assessing research performance: exploring Spanish computer science. Scientometrics Alfonso Ibáñez, Pedro Larrañaga, Concha Bielza
2013	J	`jnl`	Combinatorial Optimization by Learning and Simulation of Bayesian Networks CoRR Pedro Larrañaga, Ramon Etxeberria, José Antonio Lozano, José M. Peña
2013	J	`jnl`	Comparison of metaheuristic strategies for peakbin selection in proteomic mass spectrometry data. Inf. Sci. Miguel García-Torres, Rubén Armañanzas, Concha Bielza, Pedro Larrañaga
2013	—	`conf`	Learning Conditional Linear Gaussian Classifiers with Probabilistic Class Labels. CAEPIA Pedro L. López-Cruz, Concha Bielza, Pedro Larrañaga
2013	—	`conf`	Learning Mixtures of Polynomials of Conditional Densities from Data. CAEPIA Pedro L. López-Cruz, Thomas D. Nielsen, Concha Bielza, Pedro Larrañaga
2013	J	`jnl`	Network measures for information extraction in evolutionary algorithms. Int. J. Comput. Intell. Syst. Roberto Santana, Rubén Armañanzas, Concha Bielza, Pedro Larrañaga
2013	J	`jnl`	Parameter Control of Genetic Algorithms by Learning and Simulation of Bayesian Networks - A Case Study for the Optimal Ordering of Tables. J. Comput. Sci. Technol. Concha Bielza, Juan A. Fernández del Pozo, Pedro Larrañaga
2013	J	`jnl`	Predicting human immunodeficiency virus inhibitors using multi-dimensional Bayesian network classifiers. Artif. Intell. Medicine Hanen Borchani, Concha Bielza, Carlos Toro, Pedro Larrañaga
2013	J	`jnl`	Regularized continuous estimation of distribution algorithms. Appl. Soft Comput. Hossein Karshenas, Roberto Santana, Concha Bielza, Pedro Larrañaga
2013	J	`jnl`	Relationship among research collaboration, number of documents and number of citations: a case study in Spanish computer science production in 2000-2009. Scientometrics Alfonso Ibáñez, Concha Bielza, Pedro Larrañaga
2013	B	`conf`	Semi-supervised Projected Clustering for Classifying GABAergic Interneurons. AIME Luis Guerra, Ruth Benavides-Piccione, Concha Bielza, Víctor Robles, Javier DeFelipe, Pedro Larrañaga
2013	J	`jnl`	Sparse regularized local regression. Comput. Stat. Data Anal. Diego Vidaurre, Concha Bielza, Pedro Larrañaga
2013	—	`conf`	Towards optimal neuronal wiring through estimation of distribution algorithms. GECCO (Companion) Laura Anton-Sanchez, Concha Bielza, Pedro Larrañaga
2013	J	`jnl`	Unveiling relevant non-motor Parkinson's disease severity symptoms using a machine learning approach. Artif. Intell. Medicine Rubén Armañanzas, Concha Bielza, Kallol Ray Chaudhuri, Pablo Martínez-Martín, Pedro Larrañaga
2012	J	`jnl`	A comparison of clustering quality indices using outliers and noise. Intell. Data Anal. Luis Guerra, Víctor Robles, Concha Bielza, Pedro Larrañaga
2012	J	`jnl`	A review on probabilistic graphical models in evolutionary computation. J. Heuristics Pedro Larrañaga, Hossein Karshenas, Concha Bielza, Roberto Santana
2012	J	`jnl`	Ensemble transcript interaction networks: A case study on Alzheimer's disease. Comput. Methods Programs Biomed. Rubén Armañanzas, Pedro Larrañaga, Concha Bielza
2012	J	`jnl`	Forward stagewise naïve Bayes. Prog. Artif. Intell. Diego Vidaurre, Concha Bielza, Pedro Larrañaga
2012	J	`jnl`	Lazy lasso for local regression. Comput. Stat. Diego Vidaurre, Concha Bielza, Pedro Larrañaga
2012	J	`jnl`	Markov blanket-based approach for learning multi-dimensional Bayesian network classifiers: An application to predict the European Quality of Life-5 Dimensions (EQ-5D) from the 39-item Parkinson's Disease Questionnaire (PDQ-39). J. Biomed. Informatics Hanen Borchani, Concha Bielza, Pablo Martínez-Martín, Pedro Larrañaga
2012	—	`conf`	Maximizing the number of polychronous groups in spiking networks. GECCO (Companion) Roberto Santana, Concha Bielza, Pedro Larrañaga
2012	J	`jnl`	Regularized logistic regression and multiobjective variable selection for classifying MEG data. Biol. Cybern. Roberto Santana, Concha Bielza, Pedro Larrañaga
2012	J	`jnl`	Wrapper positive Bayesian network classifiers. Knowl. Inf. Syst. Borja Calvo, Iñaki Inza, Pedro Larrañaga, José Antonio Lozano
2011	A	`conf`	Affinity propagation enhanced by estimation of distribution algorithms. GECCO Roberto Santana, Concha Bielza, Pedro Larrañaga
2011	A*	`conf`	Bayesian Chain Classifiers for Multidimensional Classification. IJCAI Julio H. Zaragoza, Luis Enrique Sucar, Eduardo F. Morales, Concha Bielza, Pedro Larrañaga
2011	J	`jnl`	Classifying evolving data streams with partially labeled data. Intell. Data Anal. Hanen Borchani, Pedro Larrañaga, Concha Bielza
2011	J	`jnl`	Models and Simulation of 3D Neuronal Dendritic Trees Using Bayesian Networks. Neuroinformatics Pedro L. López-Cruz, Concha Bielza, Pedro Larrañaga, Ruth Benavides-Piccione, Javier DeFelipe
2011	J	`jnl`	Multi-dimensional classification with Bayesian networks. Int. J. Approx. Reason. Concha Bielza, Guangdi Li, Pedro Larrañaga
2011	C	`conf`	Multi-objective Optimization with Joint Probabilistic Modeling of Objectives and Variables. EMO Hossein Karshenas, Roberto Santana, Concha Bielza, Pedro Larrañaga
2011	J	`jnl`	Optimal row and column ordering to improve table interpretation using estimation of distribution algorithms. J. Heuristics Endika Bengoetxea, Pedro Larrañaga, Concha Bielza, Juan A. Fernández del Pozo
2011	J	`jnl`	Optimizing Brain Networks Topologies Using Multi-objective Evolutionary Computation. Neuroinformatics Roberto Santana, Concha Bielza, Pedro Larrañaga
2011	J	`jnl`	Peakbin Selection in Mass Spectrometry Data Using a Consensus Approach with Estimation of Distribution Algorithms. IEEE ACM Trans. Comput. Biol. Bioinform. Rubén Armañanzas, Yvan Saeys, Iñaki Inza, Miguel García-Torres, Concha Bielza, Yves Van de Peer, Pedro Larrañaga
2011	C	`conf`	Predicting the h-index with cost-sensitive naive Bayes. ISDA Alfonso Ibáñez, Pedro Larrañaga, Concha Bielza
2011	J	`jnl`	Probabilistic graphical models in artificial intelligence. Appl. Soft Comput. Pedro Larrañaga, Serafín Moral
2011	—	`conf`	Quantitative genetics in multi-objective optimization algorithms: from useful insights to effective methods. GECCO (Companion) Roberto Santana, Hossein Karshenas, Concha Bielza, Pedro Larrañaga
2011	A	`conf`	Regularized k-order markov models in EDAs. GECCO Roberto Santana, Hossein Karshenas, Concha Bielza, Pedro Larrañaga
2011	J	`jnl`	Regularized logistic regression without a penalty term: An application to cancer classification with microarray data. Expert Syst. Appl. Concha Bielza, Víctor Robles, Pedro Larrañaga
2011	—	`conf`	The von Mises Naive Bayes Classifier for Angular Data. CAEPIA Pedro L. López-Cruz, Concha Bielza, Pedro Larrañaga
2011	J	`jnl`	Using Bayesian networks to discover relationships between bibliometric indices. A case study of computer science and artificial intelligence journals. Scientometrics Alfonso Ibáñez, Pedro Larrañaga, Concha Bielza
2010	B	`conf`	Bivariate empirical and n-variate Archimedean copulas in estimation of distribution algorithms. IEEE Congress on Evolutionary Computation Alfredo Cuesta-Infante, Roberto Santana, José Ignacio Hidalgo, Concha Bielza, Pedro Larrañaga
2010	—	`conf`	EDA-PSO: A Hybrid Paradigm Combining Estimation of Distribution Algorithms and Particle Swarm Optimization. ANTS Conference Endika Bengoetxea, Pedro Larrañaga
2010	J	`jnl`	Learning Factorizations in Estimation of Distribution Algorithms Using Affinity Propagation. Evol. Comput. Roberto Santana, Pedro Larrañaga, José Antonio Lozano
2010	J	`jnl`	Learning an L1-Regularized Gaussian Bayesian Network in the Equivalence Class Space. IEEE Trans. Syst. Man Cybern. Part B Diego Vidaurre, Concha Bielza, Pedro Larrañaga
2010	—	`conf`	Mining Concept-Drifting Data Streams Containing Labeled and Unlabeled Instances. IEA/AIE (1) Hanen Borchani, Pedro Larrañaga, Concha Bielza
2010	J	`jnl`	Multidimensional statistical analysis of the parameterization of a genetic algorithm for the optimal ordering of tables. Expert Syst. Appl. Concha Bielza, Juan A. Fernández del Pozo, Pedro Larrañaga, Endika Bengoetxea
2010	—	`conf`	Synergies between Network-Based Representation and Probabilistic Graphical Models for Classification, Inference and Optimization Problems in Neuroscience. IEA/AIE (3) Roberto Santana, Concha Bielza, Pedro Larrañaga
2010	—	`conf`	Using Probabilistic Dependencies Improves the Search of Conductance-Based Compartmental Neuron Models. EvoBIO Roberto Santana, Concha Bielza, Pedro Larrañaga
2009	J	`jnl`	Bayesian classifiers based on kernel density estimation: Flexible classifiers. Int. J. Approx. Reason. Aritz Pérez Martínez, Pedro Larrañaga, Iñaki Inza
2009	J	`jnl`	Feature subset selection from positive and unlabelled examples. Pattern Recognit. Lett. Borja Calvo, Pedro Larrañaga, José Antonio Lozano
2009	J	`jnl`	Guest Editorial: Special Issue on Evolutionary Algorithms Based on Probabilistic Models. IEEE Trans. Evol. Comput. José Antonio Lozano, Qingfu Zhang, Pedro Larrañaga
2009	J	`jnl`	Microarray Analysis of Autoimmune Diseases by Machine Learning Procedures. IEEE Trans. Inf. Technol. Biomed. Rubén Armañanzas, Borja Calvo, Iñaki Inza, Marcos López-Hoyos, Víctor Martínez-Taboada, Eduardo Ucar, Irantzu Bernales, Asier Fullaondo, Pedro Larrañaga, Ana M. Zubiaga
2009	A	`conf`	Mining probabilistic models learned by EDAs in the optimization of multi-objective problems. GECCO Roberto Santana, Concha Bielza, José Antonio Lozano, Pedro Larrañaga
2009	J	`jnl`	Predicting citation count of Bioinform. Alfonso Ibáñez, Pedro Larrañaga, Concha Bielza
2009	—	`conf`	Probabilistic Graphical Markov Model Learning: An Adaptive Strategy. MICAI Elva Díaz, Eunice Ponce de León, Pedro Larrañaga, Concha Bielza
2009	J	`jnl`	Research topics in discrete estimation of distribution algorithms based on factorizations. Memetic Comput. Roberto Santana, Pedro Larrañaga, José Antonio Lozano
2009	J	`jnl`	Triangulation of Bayesian networks with recursive estimation of distribution algorithms. Int. J. Approx. Reason. Txomin Romero, Pedro Larrañaga
2008	J	`jnl`	A review of estimation of distribution algorithms in bioinformatics. BioData Min. Rubén Armañanzas, Iñaki Inza, Roberto Santana, Yvan Saeys, Jose Luis Flores, José Antonio Lozano, Yves Van de Peer, Rosa Blanco, Víctor Robles, Concha Bielza, Pedro Larrañaga
2008	—	`ch.`	Adaptive Estimation of Distribution Algorithms. Adaptive and Multilevel Metaheuristics Roberto Santana, Pedro Larrañaga, José Antonio Lozano
2008	A	`conf`	Adding Probabilistic Dependencies to the Search of Protein Side Chain Configurations Using EDAs. PPSN Roberto Santana, Pedro Larrañaga, José Antonio Lozano
2008	J	`jnl`	Bayesian classification for the selection of in vitro human embryos using morphological and clinical data. Comput. Methods Programs Biomed. Dinora Araceli Morales, Endika Bengoetxea, Pedro Larrañaga, Miguel García, Yosu Franco, Mónica Fresnada, Marisa Merino
2008	J	`jnl`	Combining variable neighborhood search and estimation of distribution algorithms in the protein side chain placement problem. J. Heuristics Roberto Santana, Pedro Larrañaga, José Antonio Lozano
2008	B	`conf`	Component weighting functions for adaptive search with EDAs. IEEE Congress on Evolutionary Computation Roberto Santana, Pedro Larrañaga, José Antonio Lozano
2008	J	`jnl`	Detecting reliable gene interactions by a hierarchy of Bayesian network classifiers. Comput. Methods Programs Biomed. Rubén Armañanzas, Iñaki Inza, Pedro Larrañaga
2008	J	`jnl`	Inference of Population Structure Using Genetic Markers and a Bayesian Model Averaging Approach for Clustering. J. Comput. Biol. Guzmán Santafé, José Antonio Lozano, Pedro Larrañaga
2008	J	`jnl`	Protein Folding in Simplified Models With Estimation of Distribution Algorithms. IEEE Trans. Evol. Comput. Roberto Santana, Pedro Larrañaga, José Antonio Lozano
2008	J	`jnl`	Selection of human embryos for transfer by Bayesian classifiers. Comput. Biol. Medicine Dinora Araceli Morales, Endika Bengoetxea, Pedro Larrañaga
2008	—	`ch.`	The Impact of Exact Probabilistic Learning Algorithms in EDAs Based on Bayesian Networks. Linkage in Evolutionary Computation Carlos Echegoyen, Roberto Santana, José Antonio Lozano, Pedro Larrañaga
2007	J	`jnl`	A partially supervised classification approach to dominant and recessive human disease gene prediction. Comput. Methods Programs Biomed. Borja Calvo, Núria López-Bigas, Simon J. Furney, Pedro Larrañaga, José Antonio Lozano
2007	J	`jnl`	A review of feature selection techniques in bioinformatics. Bioinform. Yvan Saeys, Iñaki Inza, Pedro Larrañaga
2007	J	`jnl`	Combining Bayesian classifiers and estimation of distribution algorithms for optimization in continuous domains. Connect. Sci. Teresa Miquélez, Endika Bengoetxea, Alexander Mendiburu, Pedro Larrañaga
2007	C	`conf`	Discriminative vs. Generative Learning of Bayesian Network Classifiers. ECSQARU Guzmán Santafé, José Antonio Lozano, Pedro Larrañaga
2007	B	`conf`	Exact Bayesian network learning in estimation of distribution algorithms. IEEE Congress on Evolutionary Computation Carlos Echegoyen, José Antonio Lozano, Roberto Santana, Pedro Larrañaga
2007	J	`jnl`	Learning Bayesian classifiers from positive and unlabeled examples. Pattern Recognit. Lett. Borja Calvo, Pedro Larrañaga, José Antonio Lozano
2007	J	`jnl`	Side chain placement using estimation of distribution algorithms. Artif. Intell. Medicine Roberto Santana, Pedro Larrañaga, José Antonio Lozano
2007	—	`conf`	The Role of a Priori Information in the Minimization of Contact Potentials by Means of Estimation of Distribution Algorithms. EvoBIO Roberto Santana, Pedro Larrañaga, José Antonio Lozano
2007	J	`jnl`	Wrapper discretization by means of estimation of distribution algorithms. Intell. Data Anal. Jose Luis Flores, Iñaki Inza, Pedro Larrañaga
2006	—	`ch.`	Bayesian Classifiers in Optimization: An EDA-like Approach. Towards a New Evolutionary Computation Teresa Miquélez, Endika Bengoetxea, Pedro Larrañaga
2006	J	`jnl`	Bayesian Model Averaging of Naive Bayes for Clustering. IEEE Trans. Syst. Man Cybern. Part B Guzmán Santafé, José Antonio Lozano, Pedro Larrañaga
2006	—	`conf`	Bayesian Model Averaging of TAN Models for Clustering. Probabilistic Graphical Models Guzmán Santafé, José Antonio Lozano, Pedro Larrañaga
2006	J	`jnl`	Discriminative Learning of Bayesian Network Classifiers. Inteligencia Artif. Guzmán Santafé, José Antonio Lozano, Pedro Larrañaga
2006	—	`conf`	Evolutionary Bayesian Classifier-Based Optimization in Continuous Domains. SEAL Teresa Miquélez, Endika Bengoetxea, Pedro Larrañaga
2006	—	`ch.`	GA-EDA: A New Hybrid Cooperative Search Evolutionary Algorithm. Towards a New Evolutionary Computation Victor Robles, José M. Peña, Pedro Larrañaga, María S. Pérez, Vanessa Herves
2006	B	`conf`	Information Theory and Classification Error in Probabilistic Classifiers. Discovery Science Aritz Pérez Martínez, Pedro Larrañaga, Iñaki Inza
2006	J	`jnl`	Machine learning in bioinformatics. Briefings Bioinform. Pedro Larrañaga, Borja Calvo, Roberto Santana, Concha Bielza, Josu Galdiano, Iñaki Inza, José Antonio Lozano, Rubén Armañanzas, Guzmán Santafé, Aritz Pérez Martínez, Victor Robles
2006	—	`conf`	Mixtures of Kikuchi Approximations. ECML Roberto Santana, Pedro Larrañaga, José Antonio Lozano
2006	J	`jnl`	Supervised classification with conditional Gaussian networks: Increasing the structure complexity from naive Bayes. Int. J. Approx. Reason. Aritz Pérez Martínez, Pedro Larrañaga, Iñaki Inza
2006	—	`book`	Towards a New Evolutionary Computation - Advances in the Estimation of Distribution Algorithms Towards a New Evolutionary Computation José Antonio Lozano, Pedro Larrañaga, Iñaki Inza, Endika Bengoetxea
2005	—	`ch.`	A Guide to the Literature on Inferring Genetic Networks by Probabilistic Graphical Models. Data Analysis and Visualization in Genomics and Proteomics Pedro Larrañaga, Iñaki Inza, Jose Luis Flores
2005	Misc	`conf`	Average Time Complexity of Estimation of Distribution Algorithms. IWANN Cristina González, A. Ramírez, José Antonio Lozano, Pedro Larrañaga
2005	C	`conf`	Discriminative Learning of Bayesian Network Classifiers via the TM Algorithm. ECSQARU Guzmán Santafé, José Antonio Lozano, Pedro Larrañaga
2005	J	`jnl`	Editorial Introduction Special Issue on Estimation of Distribution Algorithms. Evol. Comput. Pedro Larrañaga, José Antonio Lozano
2005	J	`jnl`	Editorial. Mach. Learn. Pedro Larrañaga, José Antonio Lozano, José M. Peña, Iñaki Inza
2005	J	`jnl`	Feature selection in Bayesian classifiers for the prognosis of survival of cirrhotic patients treated with TIPS. J. Biomed. Informatics Rosa Blanco, Iñaki Inza, Marisa Merino, Jorge Quiroga, Pedro Larrañaga
2005	J	`jnl`	Globally Multimodal Problem Optimization Via an Estimation of Distribution Algorithm Based on Unsupervised Learning of Bayesian Networks. Evol. Comput. José M. Peña, José Antonio Lozano, Pedro Larrañaga
2005	J	`jnl`	Inexact graph matching for model-based recognition: Evaluation and comparison of optimization algorithms. Pattern Recognit. Roberto Marcondes Cesar Junior, Endika Bengoetxea, Isabelle Bloch, Pedro Larrañaga
2005	B	`conf`	Interactions and dependencies in estimation of distribution algorithms. Congress on Evolutionary Computation Roberto Santana, Pedro Larrañaga, José Antonio Lozano
2004	J	`jnl`	Bayesian network multi-classifiers for protein secondary structure prediction. Artif. Intell. Medicine Víctor Robles, Pedro Larrañaga, José M. Peña, Ernestina Menasalvas Ruiz, María S. Pérez, Vanessa Herves, Anita Wasilewska
2004	J	`jnl`	Filter versus wrapper gene selection approaches in DNA microarray domains. Artif. Intell. Medicine Iñaki Inza, Pedro Larrañaga, Rosa Blanco, Antonio J. Cerrolaza
2004	C	`conf`	GA-EDA: Hybrid Evolutionary Algorithm Using Genetic and Estimation of Distribution Algorithms. IEA/AIE José M. Peña, Víctor Robles, Pedro Larrañaga, Vanessa Herves, Francisco Rosales, María S. Pérez
2004	J	`jnl`	Gene Selection For Cancer Classification Using Wrapper Approaches. Int. J. Pattern Recognit. Artif. Intell. Rosa Blanco, Pedro Larrañaga, Iñaki Inza, Basilio Sierra
2004	J	`jnl`	Learning Bayesian Networks In The Space Of Orderings With Estimation Of Distribution Algorithms. Int. J. Pattern Recognit. Artif. Intell. Txomin Romero, Pedro Larrañaga, Basilio Sierra
2004	—	`conf`	Protein Folding in 2-Dimensional Lattices with Estimation of Distribution Algorithms. ISBMDA Roberto Santana, Pedro Larrañaga, José Antonio Lozano
2004	—	`conf`	Selective Classifiers Can Be Too Restrictive: A Case-Study in Oesophageal Cancer. ISBMDA Rosa Blanco, Linda C. van der Gaag, Iñaki Inza, Pedro Larrañaga
2004	J	`jnl`	Unsupervised Learning Of Bayesian Networks Via Estimation Of Distribution Algorithms: An Application To Gene Expression Data Clustering. Int. J. Uncertain. Fuzziness Knowl. Based Syst. José M. Peña, José Antonio Lozano, Pedro Larrañaga
2003	J	`jnl`	Algoritmos de Estimación de Distribuciones en Problemas de Optimización Combinatoria. Inteligencia Artif. Pedro Larrañaga, José Antonio Lozano, Heinz Mühlenbein
2003	—	`conf`	Analysis of the Univariate Marginal Distribution Algorithm Modeled by Markov Chains. IWANN (1) Cristina González, Juan Diego Rodríguez, José Antonio Lozano, Pedro Larrañaga
2003	—	`conf`	Collaborative Filtering Using Interval Estimation Naïve Bayes. AWIC Víctor Robles, Pedro Larrañaga, José M. Peña, Oscar Marbán, F. Javier Crespo, María S. Pérez
2003	—	`conf`	Improvement of Naïve Bayes Collaborative Filtering Using Interval Estimation. Web Intelligence Víctor Robles, Pedro Larrañaga, Ernestina Menasalvas Ruiz, María S. Pérez, Vanessa Herves
2003	B	`conf`	Interval Estimation Naïve Bayes. IDA Víctor Robles, Pedro Larrañaga, José M. Peña, Ernestina Menasalvas Ruiz, María S. Pérez
2003	J	`jnl`	Learning Bayesian networks in the space of structures by estimation of distribution algorithms. Int. J. Intell. Syst. Rosa Blanco, Iñaki Inza, Pedro Larrañaga
2003	Misc	`conf`	Learning Semi Naïve Bayes Structures by Estimation of Distribution Algorithms. EPIA Víctor Robles, Pedro Larrañaga, José M. Peña, María S. Pérez, Ernestina Menasalvas Ruiz, Vanessa Herves
2003	Misc	`conf`	Parallel Stochastic Search for Protein Secondary Structure Prediction. PPAM Víctor Robles, María S. Pérez, Vanessa Herves, José M. Peña, Pedro Larrañaga
2002	—	`ch.`	A Review on Estimation of Distribution Algorithms. Estimation of Distribution Algorithms Pedro Larrañaga
2002	—	`ch.`	Adjusting Weights in Artificial Neural Networks using Evolutionary Algorithms. Estimation of Distribution Algorithms Carlos Cotta, Enrique Alba, Ramón Sagarna, Pedro Larrañaga
2002	—	`ch.`	An Empirical Comparison Between K-Means, GAs and EDAs in Partitional Clustering. Estimation of Distribution Algorithms Josep Roure, Pedro Larrañaga, Ramon Sangüesa
2002	—	`ch.`	An Introduction to Probabilistic Graphical Models. Estimation of Distribution Algorithms Pedro Larrañaga
2002	—	`ch.`	Benefits of Data Clustering in Multimodal Function Optimization via EDAs. Estimation of Distribution Algorithms José M. Peña, José Antonio Lozano, Pedro Larrañaga
2002	—	`book`	Estimation of Distribution Algorithms Pedro Larrañaga, José Antonio Lozano
2002	—	`ch.`	Experimental Results in Function Optimization with EDAs in Continuous Domain. Estimation of Distribution Algorithms Endika Bengoetxea, Teresa Miquélez, Pedro Larrañaga, José Antonio Lozano
2002	—	`ch.`	Feature Subset Selection by Estimation of Distribution Algorithms. Estimation of Distribution Algorithms Iñaki Inza, Pedro Larrañaga, Basilio Sierra
2002	—	`ch.`	Feature Weighting for Nearest Neighbor by Estimation of Distribution Algorithms. Estimation of Distribution Algorithms Iñaki Inza, Pedro Larrañaga, Basilio Sierra
2002	—	`conf`	Floating Search Methods in Learning Bayesian Networks. Probabilistic Graphical Models Rosa Blanco, Iñaki Inza, Pedro Larrañaga
2002	J	`jnl`	Inexact graph matching by means of estimation of distribution algorithms. Pattern Recognit. Endika Bengoetxea, Pedro Larrañaga, Isabelle Bloch, Aymeric Perchant, Claudia Boeres
2002	J	`jnl`	Learning Recursive Bayesian Multinets for Data Clustering by Means of Constructive Induction. Mach. Learn. José M. Peña, José Antonio Lozano, Pedro Larrañaga
2002	—	`ch.`	Mathematical Modeling of Discrete Estimation of Distribution Algorithms. Estimation of Distribution Algorithms Cristina González, José Antonio Lozano, Pedro Larrañaga
2002	J	`jnl`	Mathematical modelling of UMDA Int. J. Approx. Reason. Cristina González, José Antonio Lozano, Pedro Larrañaga
2002	—	`ch.`	Parallel Estimation of Distribution Algorithms. Estimation of Distribution Algorithms José Antonio Lozano, Ramón Sagarna, Pedro Larrañaga
2002	—	`ch.`	Partial Abductive Inference in Bayesian Networks: An Empirical Comparison Between GAs and EDAs. Estimation of Distribution Algorithms L. M. Campos, José A. Gámez, Pedro Larrañaga, Serafín Moral, Txomin Romero
2002	—	`ch.`	Rule Induction by Estimation of Distribution Algorithms. Estimation of Distribution Algorithms Basilio Sierra, E. A. Jiménez, Iñaki Inza, Pedro Larrañaga, J. Muruzábal
2002	—	`ch.`	Solving Graph Matching with EDAs Using a Permutation-Based Representation. Estimation of Distribution Algorithms Endika Bengoetxea, Pedro Larrañaga, Aymeric Perchant, Isabelle Bloch
2002	—	`ch.`	Solving the 0-1 Knapsack Problem with EDAs. Estimation of Distribution Algorithms Ramón Sagarna, Pedro Larrañaga
2002	—	`ch.`	Solving the Traveling Salesman Problem with EDAs. Estimation of Distribution Algorithms Víctor Robles, P. de Miguel, Pedro Larrañaga
2002	J	`jnl`	Synergies between evolutionary computation and probabilistic graphical models. Int. J. Approx. Reason. Pedro Larrañaga, José Antonio Lozano
2002	—	`conf`	Unsupervised Learning of Bayesian Networks Via Estimation of Distribution Algorithms. Probabilistic Graphical Models José M. Peña, José Antonio Lozano, Pedro Larrañaga
2001	J	`jnl`	Dimensionality Reduction in Unsupervised Learning of Conditional Gaussian Networks. IEEE Trans. Pattern Anal. Mach. Intell. José M. Peña, José Antonio Lozano, Pedro Larrañaga, Iñaki Inza
2001	—	`conf`	Estimation of Distribution Algorithms: A New Evolutionary Computation Approach for Graph Matching Problems. EMMCVPR Endika Bengoetxea, Pedro Larrañaga, Isabelle Bloch, Aymeric Perchant
2001	J	`jnl`	Feature subset selection by Bayesian networks: a comparison with genetic and sequential algorithms. Int. J. Approx. Reason. Iñaki Inza, Pedro Larrañaga, Basilio Sierra
2001	J	`jnl`	Feature subset selection by genetic algorithms and estimation of distribution algorithms - A case study in the survival of cirrhotic patients treated with TIPS. Artif. Intell. Medicine Iñaki Inza, Marisa Merino, Pedro Larrañaga, Jorge Quiroga, Basilio Sierra, Marcos Girala
2001	A	`conf`	Geographical clustering of cancer incidence by means of Bayesian networks and conditional Gaussian networks. AISTATS José M. Peña, I. Izarzugaza, José Antonio Lozano, E. Aldasoro, Pedro Larrañaga
2001	—	`conf`	On Applying Supervised Classification Techniques in Medicine. ISMDA Basilio Sierra, Iñaki Inza, Pedro Larrañaga
2001	J	`jnl`	Performance evaluation of compromise conditional Gaussian networks for data clustering. Int. J. Approx. Reason. José M. Peña, José Antonio Lozano, Pedro Larrañaga
2001	B	`conf`	Prototype Selection and Feature Subset Selection by Estimation of Distribution Algorithms. A Case Study in the Survival of Cirrhotic Patients Treated with TIPS. AIME Basilio Sierra, Elena Lazkano, Iñaki Inza, Marisa Merino, Pedro Larrañaga, Jorge Quiroga
2001	J	`jnl`	Using Bayesian networks in the construction of a bi-level multi-classifier. A case study using intensive care unit patients data. Artif. Intell. Medicine Basilio Sierra, Nicolás Serrano, Pedro Larrañaga, Eliseo J. Plasencia, Iñaki Inza, Juan José Jiménez, Pedro Revuelta, María Luisa Mora
2000	J	`jnl`	An improved Bayesian structural EM algorithm for learning Bayesian networks for clustering. Pattern Recognit. Lett. José M. Peña, José Antonio Lozano, Pedro Larrañaga
2000	J	`jnl`	Analyzing the Population Based Incremental Learning Algorithm by Means of Discrete Dynamical Systems. Complex Syst. Cristina González, José Antonio Lozano, Pedro Larrañaga
2000	A	`conf`	Combinatonal Optimization by Learning and Simulation of Bayesian Networks. UAI Pedro Larrañaga, Ramon Etxeberria, José Antonio Lozano, José M. Peña
2000	—	`conf`	Feature Subset Selection Using Probabilistic Tree Structures. A Case Study in the Survival of Cirrhotic Patients Treated with TIPS. ISMDA Iñaki Inza, Marisa Merino, Pedro Larrañaga, Jorge Quiroga, Basilio Sierra, Marcos Girala
2000	J	`jnl`	Feature Subset Selection by Bayesian network-based optimization. Artif. Intell. Iñaki Inza, Pedro Larrañaga, Ramon Etxeberria, Basilio Sierra
2000	—	`conf`	Medical Bayes Networks. ISMDA Basilio Sierra, Iñaki Inza, Pedro Larrañaga
1999	J	`jnl`	An empirical comparison of four initialization methods for the K-Means algorithm. Pattern Recognit. Lett. José M. Peña, José Antonio Lozano, Pedro Larrañaga
1999	J	`jnl`	Applying genetic algorithms to search for the best hierarchical clustering of a dataset. Pattern Recognit. Lett. José Antonio Lozano, Pedro Larrañaga
1999	J	`jnl`	Genetic Algorithms for the Travelling Salesman Problem: A Review of Representations and Operators. Artif. Intell. Rev. Pedro Larrañaga, Cindy M. H. Kuijpers, Roberto H. Murga, Iñaki Inza, S. Dizdarevic
1999	J	`jnl`	Genetic Algorithms: Bridging the Convergence Gap. Theor. Comput. Sci. José Antonio Lozano, Pedro Larrañaga, Manuel Graña, F. Xabier Albizuri
1999	J	`jnl`	Learning Bayesian networks for clustering by means of constructive induction. Pattern Recognit. Lett. José M. Peña, José Antonio Lozano, Pedro Larrañaga
1999	—	`conf`	Machine Learning Inspired Approaches to Combine Standard Medical Measures at an Intensive Care Unit. AIMDM Basilio Sierra, Nicolás Serrano, Pedro Larrañaga, Eliseo J. Plasencia, Iñaki Inza, Juan José Jiménez, Jose María De la Rosa, María Luisa Mora
1999	J	`jnl`	Representing the behaviour of supervised classification learning algorithms by Bayesian networks. Pattern Recognit. Lett. Iñaki Inza, Pedro Larrañaga, Basilio Sierra, Ramon Etxeberria, José Antonio Lozano, José M. Peña
1998	J	`jnl`	Aplicación de los algoritmos genéticos al problema del clustering jerárquico. Inteligencia Artif. José Antonio Lozano, Pedro Larrañaga
1998	J	`jnl`	Predicting survival in malignant skin melanoma using Bayesian networks automatically induced by genetic algorithms. An empirical comparison between different approaches. Artif. Intell. Medicine Basilio Sierra, Pedro Larrañaga
1997	J	`jnl`	Analysis of the behaviour of genetic algorithms when learning Bayesian network structure from data. Pattern Recognit. Lett. Ramon Etxeberria, Pedro Larrañaga, Juan M. Picaza
1997	Misc	`conf`	Bayesian Networks, Rule Induction and Logistic Regression in the Prediction of the Survival of Women Suffering from Breast Cancer. EPIA Pedro Larrañaga, Miren J. Gallego, Basilio Sierra, L. Urkola, Maria J. Michelena
1997	J	`jnl`	Decomposing Bayesian networks: triangulation of the moral graph with genetic algorithms. Stat. Comput. Pedro Larrañaga, Cindy M. H. Kuijpers, Mikel Poza, Roberto H. Murga
1997	—	`conf`	Experimental Results of a Michigan-like Evolution Strategy for Non-stationary Clustering. ICANNGA Ana Isabel González, Manuel Graña, José Antonio Lozano, Pedro Larrañaga
1997	B	`conf`	Learning Bayesisan Networks by Genetic Algorithms: A Case Study in the Prediction of Survival in Malignant Skin Melanoma. AIME Pedro Larrañaga, Basilio Sierra, Miren J. Gallego, Maria J. Michelena, Juan M. Picaza
1997	J	`jnl`	Structure of the high-order Boltzmann machine from independence maps. IEEE Trans. Neural Networks F. Xabier Albizuri, Alicia D'Anjou, Manuel Graña, Pedro Larrañaga
1996	J	`jnl`	Learning Bayesian network structures by searching for the best ordering with genetic algorithms. IEEE Trans. Syst. Man Cybern. Part A Pedro Larrañaga, Cindy M. H. Kuijpers, Roberto H. Murga, Yosu Yurramendi
1996	J	`jnl`	Structure Learning of Bayesian Networks by Genetic Algorithms: A Performance Analysis of Control Parameters. IEEE Trans. Pattern Anal. Mach. Intell. Pedro Larrañaga, Mikel Poza, Yosu Yurramendi, Roberto H. Murga, Cindy M. H. Kuijpers
1995	A	`conf`	Structure Learning of Bayesian Networks by Hybrid Genetic Algorithms. AISTATS Pedro Larrañaga, Roberto H. Murga, Mikel Poza, Cindy M. H. Kuijpers
1993	—	`conf`	Genetic Algorithms Elitist Probabilistic of Degree 1, a generalization of Simulated Annealing. AI*IA Pedro Larrañaga, Manuel Graña, Alicia D'Anjou, Francisco Javier Torrealdea
1993	C	`conf`	Structure learning approaches in Causal Probalistics Networks. ECSQARU Pedro Larrañaga, Yosu Yurramendi