Concha Bielza - RankMe

186 papers A* 1A 6B 6C 4Misc 2Journal 127Unranked 39

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Bandwidth selectors on semiparametric Bayesian networks. Inf. Sci. Victor Alejandre, Concha Bielza, Pedro Larrañaga
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`	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`	Guest Editors introduction: special issue of the ECMLPKDD 2015 journal track. Mach. Learn. Concha Bielza, João Gama, Alípio Jorge, Indre Zliobaite
2015	J	`jnl`	Guest editors introduction: special issue of the ECMLPKDD 2015 journal track. Data Min. Knowl. Discov. Concha Bielza, João Gama, Alípio Jorge, Indre Zliobaite
2015	J	`jnl`	Interval-based ranking in noisy evolutionary multi-objective optimization. Comput. Optim. Appl. Hossein Karshenas, Concha Bielza, Pedro Larrañaga
2015	J	`jnl`	Recent Advances in Probabilistic Graphical Models. Int. J. Intell. Syst. Concha Bielza, Serafín Moral, Antonio Salmerón
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 review on evolutionary algorithms in Bayesian network learning and inference tasks. Inf. Sci. Pedro Larrañaga, Hossein Karshenas, Concha Bielza, Roberto Santana
2013	—	`ed.`	Advances in Artificial Intelligence - 15th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2013, Madrid, Spain, September 17-20, 2013. Proceedings CAEPIA Concha Bielza, Antonio Salmerón, Amparo Alonso-Betanzos, José Ignacio Hidalgo, Luis Martínez-López, Alicia Troncoso Lora, Emilio Corchado, Juan M. Corchado
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`	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
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`	Dealing with complex queries in decision-support systems. Data Knowl. Eng. Juan A. Fernández del Pozo, 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	—	`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	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`	Modeling challenges with influence diagrams: Constructing probability and utility models. Decis. Support Syst. Concha Bielza, Manuel Gómez, Prakash P. Shenoy
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`	Comparison of Bayesian networks and artificial neural networks for quality detection in a machining process. Expert Syst. Appl. Maritza Correa, Concha Bielza, J. Pamies-Teixeira
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
2008	J	`jnl`	A Bayesian network model for surface roughness prediction in the machining process. Int. J. Syst. Sci. Maritza Correa, Concha Bielza, M. de J. Ramirez, José R. Alique
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	J	`jnl`	Explaining clinical decisions by extracting regularity patterns. Decis. Support Syst. Concha Bielza, Juan A. Fernández del Pozo, Peter J. F. Lucas
2006	J	`jnl`	A decision approach to competitive electronic sealed-bid auctions for land. J. Oper. Res. Soc. Enrique Ballestero, Concha Bielza, David Pla-Santamaria
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
2005	J	`jnl`	A list-based compact representation for large decision tables management. Eur. J. Oper. Res. Juan A. Fernández del Pozo, Concha Bielza, Manuel Gómez
2004	J	`jnl`	Node deletion sequences in influence diagrams using genetic algorithms. Stat. Comput. Manuel Gómez, Concha Bielza
2003	B	`conf`	Finding and Explaining Optimal Treatments. AIME Concha Bielza, Juan A. Fernández del Pozo, Peter J. F. Lucas
2003	—	`conf`	Optimal Decision Explanation by Extracting Regularity Patterns. SGAI Conf. Concha Bielza, Juan A. Fernández del Pozo, Peter J. F. Lucas
2002	—	`conf`	An Interactive Framework for Open Queries in Decision Support Systems. IBERAMIA Juan A. Fernández del Pozo, Concha Bielza
2002	—	`conf`	Inferentially Efficient Propagation in Non-Decomposable Bayesian Network with Hierarchical Junction Trees. Probabilistic Graphical Models Roberto O. Puch, Jim Q. Smith, Concha Bielza
2002	—	`conf`	New Structures for Conditional Probability Tables. Probabilistic Graphical Models Juan A. Fernández del Pozo, Concha Bielza
2001	—	`conf`	Knowledge Organisation in a Neonatal Jaundice Decision Support System. ISMDA Juan A. Fernández del Pozo, Concha Bielza, Manuel Gómez
2000	J	`jnl`	Structural, elicitation and computational issues faced when solving complex decision making problems with influence diagrams. Comput. Oper. Res. Concha Bielza, Manuel Gómez, Sixto Ríos-Insua, Juan A. Fernández del Pozo
1999	—	`conf`	Influence Diagrams for Neonatal Jaundice Management. AIMDM Concha Bielza, Sixto Ríos-Insua, Manuel Gómez
1997	A	`conf`	A Comparison of Decision Trees, Influence Diagrams and Valuation Networks for Asymmetric Decision Problems. AISTATS Concha Bielza, Prakash P. Shenoy
1997	A	`conf`	Markov chain Monte Carlo methods for decision analysis. AISTATS Concha Bielza, Peter Müller, David Ríos Insua