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Concepcion Bielza
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- affiliation: Universidad Politécnica de Madrid
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2020 – today
- 2024
[j110]Vicente P. Soloviev
, Pedro Larrañaga, Concha Bielza:
EDAspy: An extensible python package for estimation of distribution algorithms. Neurocomputing 598: 128043 (2024)- [j109]Vicente P. Soloviev, Concha Bielza, Pedro Larrañaga:
Semiparametric Estimation of Distribution Algorithms for Continuous Optimization. IEEE Trans. Evol. Comput. 28(4): 1069-1083 (2024) - [j108]Pedro Larrañaga, Concha Bielza:
Estimation of Distribution Algorithms in Machine Learning: A Survey. IEEE Trans. Evol. Comput. 28(5): 1301-1321 (2024) - [j107]Carlos Puerto-Santana, Pedro Larrañaga, Concha Bielza:
Feature Saliencies in Asymmetric Hidden Markov Models. IEEE Trans. Neural Networks Learn. Syst. 35(3): 3586-3600 (2024) - 2023
- [j106]Carlos Villa-Blanco, Concha Bielza, Pedro Larrañaga:
Feature subset selection for data and feature streams: a review. Artif. Intell. Rev. 56(S1): 1011-1062 (2023) - [j105]Gabriel Valverde, David Quesada, Pedro Larrañaga, Concha Bielza:
Causal reinforcement learning based on Bayesian networks applied to industrial settings. Eng. Appl. Artif. Intell. 125: 106657 (2023) - [j104]Carlos Villa-Blanco, Alessandro Bregoli, Concha Bielza, Pedro Larrañaga, Fabio Stella:
Constraint-based and hybrid structure learning of multidimensional continuous-time Bayesian network classifiers. Int. J. Approx. Reason. 159: 108945 (2023) - [j103]Enrique Valero-Leal, Concha Bielza, Pedro Larrañaga, Silja Renooij:
Efficient search for relevance explanations using MAP-independence in Bayesian networks. Int. J. Approx. Reason. 160: 108965 (2023) - [j102]Carlos Puerto-Santana, Pedro Larrañaga, Concha Bielza:
Feature subset selection in data-stream environments using asymmetric hidden Markov models and novelty detection. Neurocomputing 554: 126641 (2023) - [j101]Nikolas Bernaola, Mario Michiels, Pedro Larrañaga, Concha Bielza:
Learning massive interpretable gene regulatory networks of the human brain by merging Bayesian networks. PLoS Comput. Biol. 19(12) (2023) - [j100]Vicente P. Soloviev, Concha Bielza, Pedro Larrañaga:
Quantum approximate optimization algorithm for Bayesian network structure learning. Quantum Inf. Process. 22(1): 19 (2023) - [c57]Vicente P. Soloviev, Pedro Larrañaga, Concha Bielza:
Variational Quantum Algorithm Parameter Tuning with Estimation of Distribution Algorithms. CEC 2023: 1-9 - [c56]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:
High-Dimensional Feature Characterization of Single Nucleotide Variants in Hypertrophic Cardiomyopathy. CinC 2023: 1-4 - [c55]Jorge Casajús-Setién, Concha Bielza, Pedro Larrañaga:
Anomaly-Based Intrusion Detection in IIoT Networks Using Transformer Models. CSR 2023: 72-77 - [i10]Carlos Puerto-Santana, Concha Bielza, Pedro Larrañaga, Gustav Eje Henter:
Context-specific kernel-based hidden Markov model for time series analysis. CoRR abs/2301.09870 (2023) - [i9]David Quesada, Pedro Larrañaga, Concha Bielza:
Classifying the evolution of COVID-19 severity on patients with combined dynamic Bayesian networks and neural networks. CoRR abs/2303.05972 (2023) - 2022
- [j99]Fernando Rodriguez-Sanchez, Concha Bielza, Pedro Larrañaga:
Multipartition clustering of mixed data with Bayesian networks. Int. J. Intell. Syst. 37(3): 2188-2218 (2022) - [j98]David Quesada, Concha Bielza, Pedro Fontán, Pedro Larrañaga:
Piecewise forecasting of nonlinear time series with model tree dynamic Bayesian networks. Int. J. Intell. Syst. 37(11): 9108-9137 (2022) - [j97]David Atienza, Concha Bielza, Pedro Larrañaga:
PyBNesian: An extensible python package for Bayesian networks. Neurocomputing 504: 204-209 (2022) - [j96]Carlos Puerto-Santana, Concha Bielza, Javier Diaz-Rozo, Guillem Ramirez-Gargallo, Filippo Mantovani, Gaizka Virumbrales, Jesús Labarta, Pedro Larrañaga:
Asymmetric HMMs for Online Ball-Bearing Health Assessments. IEEE Internet Things J. 9(20): 20160-20177 (2022) - [j95]David Atienza, Concha Bielza, Pedro Larrañaga:
Semiparametric Bayesian networks. Inf. Sci. 584: 564-582 (2022) - [j94]Vicente P. Soloviev, Pedro Larrañaga, Concha Bielza:
Estimation of distribution algorithms using Gaussian Bayesian networks to solve industrial optimization problems constrained by environment variables. J. Comb. Optim. 44(2): 1077-1098 (2022) - [j93]Carlos Puerto-Santana, Pedro Larrañaga, Concha Bielza:
Autoregressive Asymmetric Linear Gaussian Hidden Markov Models. IEEE Trans. Pattern Anal. Mach. Intell. 44(9): 4642-4658 (2022) - [c54]Vicente P. Soloviev, Pedro Larrañaga, Concha Bielza:
Quantum parametric circuit optimization with estimation of distribution algorithms. GECCO Companion 2022: 2247-2250 - [c53]Carlos Villa-Blanco, Alessandro Bregoli, Concha Bielza, Pedro Larrañaga, Fabio Stella:
Structure learning algorithms for multidimensional continuous-time Bayesian network classifiers. PGM 2022: 313-324 - [c52]Enrique Valero-Leal, Pedro Larrañaga, Concha Bielza:
Interpreting Time-Varying Dynamic Bayesian Networks for Earth Climate Modelling. PGM 2022: 373-384 - [c51]Jorge Casajús-Setién, Concha Bielza, Pedro Larrañaga:
Evolutive Adversarially-Trained Bayesian Network Autoencoder for Interpretable Anomaly Detection. PGM 2022: 397-408 - [d1]David Atienza, Concha Bielza, Javier Diaz-Rozo, Pedro Larrañaga:
Anomaly Detection with Laser Heat Treatment Thermal Videos. IEEE DataPort, 2022
- [i8]Vicente P. Soloviev, Concha Bielza, Pedro Larrañaga:
Quantum Approximate Optimization Algorithm for Bayesian network structure learning. CoRR abs/2203.02400 (2022) - 2021
- [j92]Santiago Gil-Begue, Concha Bielza, Pedro Larrañaga:
Multi-dimensional Bayesian network classifiers: A survey. Artif. Intell. Rev. 54(1): 519-559 (2021) - [j91]David Quesada, Gabriel Valverde, Pedro Larrañaga, Concha Bielza:
Long-term forecasting of multivariate time series in industrial furnaces with dynamic Gaussian Bayesian networks. Eng. Appl. Artif. Intell. 103: 104301 (2021) - [j90]Bojan Mihaljevic, Pedro Larrañaga, Concha Bielza:
Comparing the Electrophysiology and Morphology of Human and Mouse Layer 2/3 Pyramidal Neurons With Bayesian Networks. Frontiers Neuroinformatics 15: 580873 (2021) - [j89]Carlos Villa-Blanco, Pedro Larrañaga, Concha Bielza:
Multidimensional continuous time Bayesian network classifiers. Int. J. Intell. Syst. 36(12): 7839-7866 (2021) - [j88]Mario Michiels, Pedro Larrañaga, Concha Bielza:
BayeSuites: An open web framework for massive Bayesian networks focused on neuroscience. Neurocomputing 428: 166-181 (2021) - [j87]Bojan Mihaljevic, Concha Bielza, Pedro Larrañaga:
Bayesian networks for interpretable machine learning and optimization. Neurocomputing 456: 648-665 (2021) - [c50]Vicente P. Soloviev, Concha Bielza, Pedro Larrañaga:
Quantum-Inspired Estimation Of Distribution Algorithm To Solve The Travelling Salesman Problem. CEC 2021: 416-425 - [c49]David Quesada, Concha Bielza, Pedro Larrañaga:
Structure Learning of High-Order Dynamic Bayesian Networks via Particle Swarm Optimization with Order Invariant Encoding. HAIS 2021: 158-171 - [c48]Carlos Puerto-Santana, Pedro Larrañaga, Javier Diaz-Rozo, Concha Bielza:
An Online Feature Selection Methodology for Ball-Bearing Harmonic Frequencies Based on HMMs. SOCO 2021: 546-555 - [i7]David Atienza, Concha Bielza, Pedro Larrañaga:
Semiparametric Bayesian Networks. CoRR abs/2109.03008 (2021) - 2020
- [j86]Irene Córdoba, Concha Bielza, Pedro Larrañaga, Gherardo Varando:
Sparse Cholesky Covariance Parametrization for Recovering Latent Structure in Ordered Data. IEEE Access 8: 154614-154624 (2020) - [j85]Fernando Rodriguez-Sanchez, Pedro Larrañaga, Concha Bielza:
Incremental Learning of Latent Forests. IEEE Access 8: 224420-224432 (2020) - [j84]Javier Diaz-Rozo, Concha Bielza, Pedro Larrañaga:
Machine-tool condition monitoring with Gaussian mixture models-based dynamic probabilistic clustering. Eng. Appl. Artif. Intell. 89: 103434 (2020) - [j83]Irene Córdoba, Gherardo Varando, Concha Bielza, Pedro Larrañaga:
On generating random Gaussian graphical models. Int. J. Approx. Reason. 125: 240-250 (2020) - [c47]Nikolas Bernaola, Mario Michiels, Concha Bielza, Pedro Larrañaga:
BayesSuites: An Open Web Framework for Visualization of Massive Bayesian Networks. PGM 2020: 593-596 - [i6]Irene Córdoba, Concha Bielza, Pedro Larrañaga, Gherardo Varando:
Sparse Cholesky covariance parametrization for recovering latent structure in ordered data. CoRR abs/2006.01448 (2020) - [i5]Carlos Puerto-Santana, Pedro Larrañaga, Concha Bielza:
Autoregressive Asymmetric Linear Gaussian Hidden Markov Models. CoRR abs/2010.15604 (2020)
2010 – 2019
- 2019
- [j82]Pablo Fernandez-Gonzalez, Concepcion Bielza, Pedro Larrañaga:
Random Forests for Regression as a Weighted Sum of ${k}$ -Potential Nearest Neighbors. IEEE Access 7: 25660-25672 (2019) - [j81]Sergio Luengo-Sanchez, Pedro Larrañaga, Concha Bielza:
A Directional-Linear Bayesian Network and Its Application for Clustering and Simulation of Neural Somas. IEEE Access 7: 69907-69921 (2019) - [j80]Marco Benjumeda, Concha Bielza, Pedro Larrañaga:
Learning tractable Bayesian networks in the space of elimination orders. Artif. Intell. 274: 66-90 (2019) - [j79]Ignacio Leguey, Concha Bielza, Pedro Larrañaga:
Circular Bayesian classifiers using wrapped Cauchy distributions. Data Knowl. Eng. 122: 101-115 (2019) - [j78]Ignacio Leguey, Pedro Larrañaga, Concha Bielza, Shogo Kato:
A circular-linear dependence measure under Johnson-Wehrly distributions and its application in Bayesian networks. Inf. Sci. 486: 240-253 (2019) - [j77]Marco Benjumeda, Sergio Luengo-Sanchez, Pedro Larrañaga, Concha Bielza:
Tractable learning of Bayesian networks from partially observed data. Pattern Recognit. 91: 190-199 (2019) - 2018
- [j76]Bojan Mihaljevic, Pedro Larrañaga, Ruth Benavides-Piccione, Sean L. Hill, Javier DeFelipe, Concha Bielza:
Towards a supervised classification of neocortical interneuron morphologies. BMC Bioinform. 19(1): 511:1-511:22 (2018) - [j75]Marco Benjumeda, Concha Bielza, Pedro Larrañaga:
Tractability of most probable explanations in multidimensional Bayesian network classifiers. Int. J. Approx. Reason. 93: 74-87 (2018) - [j74]Javier Diaz-Rozo, Concha Bielza, Pedro Larrañaga:
Clustering of Data Streams With Dynamic Gaussian Mixture Models: An IoT Application in Industrial Processes. IEEE Internet Things J. 5(5): 3533-3547 (2018) - [j73]Sergio Luengo-Sanchez, Isabel Fernaud, Concha Bielza, Ruth Benavides-Piccione, Pedro Larrañaga, Javier DeFelipe:
3D morphology-based clustering and simulation of human pyramidal cell dendritic spines. PLoS Comput. Biol. 14(6) (2018) - [j72]Laura Anton-Sanchez, Felix Effenberger, Concha Bielza, Pedro Larrañaga, Hermann Cuntz:
A regularity index for dendrites - local statistics of a neuron's input space. PLoS Comput. Biol. 14(11) (2018) - [j71]Bojan Mihaljevic, Concha Bielza, Pedro Larrañaga:
bnclassify: Learning Bayesian Network Classifiers. R J. 10(2): 455 (2018) - [c46]Irene Córdoba, Eduardo C. Garrido-Merchán, Daniel Hernández-Lobato, Concha Bielza, Pedro Larrañaga:
Bayesian Optimization of the PC Algorithm for Learning Gaussian Bayesian Networks. CAEPIA 2018: 44-54 - [c45]Carlos Puerto-Santana, Concha Bielza, Pedro Larrañaga:
Asymmetric Hidden Markov Models with Continuous Variables. CAEPIA 2018: 98-107 - [c44]Irene Córdoba, Gherardo Varando, Concha Bielza, Pedro Larrañaga:
A Fast Metropolis-Hastings Method for Generating Random Correlation Matrices. IDEAL (1) 2018: 117-124 - [c43]Santiago Gil-Begue, Pedro Larrañaga, Concha Bielza:
Multi-dimensional Bayesian Network Classifier Trees. IDEAL (1) 2018: 354-363 - [c42]Irene Córdoba, Gherardo Varando, Concha Bielza, Pedro Larrañaga:
A partial orthogonalization method for simulating covariance and concentration graph matrices. PGM 2018: 61-72 - [c41]Bojan Mihaljevic, Concha Bielza, Pedro Larrañaga:
Learning Bayesian network classifiers with completed partially directed acyclic graphs. PGM 2018: 272-283 - [c40]Fernando Rodriguez-Sanchez, Pedro Larrañaga, Concha Bielza:
Discrete model-based clustering with overlapping subsets of attributes. PGM 2018: 392-403 - [i4]Irene Córdoba-Sánchez, Eduardo C. Garrido-Merchán, Daniel Hernández-Lobato, Concha Bielza, Pedro Larrañaga:
Bayesian optimization of the PC algorithm for learning Gaussian Bayesian networks. CoRR abs/1806.11015 (2018) - [i3]Gherardo Varando, Concha Bielza, Pedro Larrañaga, Eva Riccomagno:
Markov Property in Generative Classifiers. CoRR abs/1811.04759 (2018) - [i2]Irene Córdoba, Concha Bielza, Pedro Larrañaga:
Towards Gaussian Bayesian Network Fusion. CoRR abs/1812.00262 (2018) - 2017
- [j70]Laura Anton-Sanchez, Concha Bielza, Pedro Larrañaga:
Network design through forests with degree- and role-constrained minimum spanning trees. J. Heuristics 23(1): 31-51 (2017) - [j69]Luis Rodriguez-Lujan, Pedro Larrañaga, Concha Bielza:
Frobenius Norm Regularization for the Multivariate Von Mises Distribution. Int. J. Intell. Syst. 32(2): 153-176 (2017) - [j68]Pablo Fernandez-Gonzalez, Concha Bielza, Pedro Larrañaga:
Univariate and bivariate truncated von Mises distributions. Prog. Artif. Intell. 6(2): 171-180 (2017) - [c39]Javier Mesonero, Concha Bielza, Pedro Larrañaga:
Architecture for anomaly detection in a laser heating surface process. ETFA 2017: 1-4 - 2016
- [j67]Hanen Borchani, Pedro Larrañaga, João Gama, Concha Bielza:
Mining multi-dimensional concept-drifting data streams using Bayesian network classifiers. Intell. Data Anal. 20(2): 257-280 (2016) - [j66]Gherardo Varando, Concha Bielza, Pedro Larrañaga:
Decision functions for chain classifiers based on Bayesian networks for multi-label classification. Int. J. Approx. Reason. 68: 164-178 (2016) - [j65]Alfonso Ibáñez, Rubén Armañanzas, Concha Bielza, Pedro Larrañaga:
Genetic algorithms and Gaussian Bayesian networks to uncover the predictive core set of bibliometric indices. J. Assoc. Inf. Sci. Technol. 67(7): 1703-1721 (2016) - [j64]Laura Anton-Sanchez, Concha Bielza, Ruth Benavides-Piccione, Javier DeFelipe, Pedro Larrañaga:
Dendritic and Axonal Wiring Optimization of Cortical GABAergic Interneurons. Neuroinformatics 14(4): 453-464 (2016) - [j63]Marco Benjumeda, Pedro Larrañaga, Concha Bielza:
Learning Bayesian networks with low inference complexity. Prog. Artif. Intell. 5(1): 15-26 (2016) - [c38]Ignacio Leguey, Concha Bielza, Pedro Larrañaga:
Tree-Structured Bayesian Networks for Wrapped Cauchy Directional Distributions. CAEPIA 2016: 207-216 - [c37]Sergio Luengo-Sanchez, Concha Bielza, Pedro Larrañaga:
Hybrid Gaussian and von Mises Model-Based Clustering. ECAI 2016: 855-862 - [c36]Alberto Ogbechie, Javier Diaz-Rozo, Pedro Larrañaga, Concha Bielza:
Dynamic Bayesian Network-Based Anomaly Detection for In-Process Visual Inspection of Laser Surface Heat Treatment. ML4CPS 2016: 17-24 - [c35]Marco Benjumeda, Concha Bielza, Pedro Larrañaga:
Learning Tractable Multidimensional Bayesian Network Classifiers. Probabilistic Graphical Models 2016: 13-24 - [c34]David Atienza, Concha Bielza, Javier Díaz, Pedro Larrañaga:
Anomaly Detection with a Spatio-Temporal Tracking of the Laser Spot. STAIRS 2016: 137-142 - [i1]Irene Córdoba-Sánchez, Concha Bielza, Pedro Larrañaga:
A review of undirected and acyclic directed Gaussian Markov model selection and estimation. CoRR abs/1606.07282 (2016) - 2015
- [j62]Bojan Mihaljevic, Ruth Benavides-Piccione, Luis Guerra, Javier DeFelipe, Pedro Larrañaga, Concha Bielza:
Classifying GABAergic interneurons with semi-supervised projected model-based clustering. Artif. Intell. Medicine 65(1): 49-59 (2015) - [j61]Hossein Karshenas, Concha Bielza, Pedro Larrañaga:
Interval-based ranking in noisy evolutionary multi-objective optimization. Comput. Optim. Appl. 61(2): 517-555 (2015) - [j60]Concha Bielza, João Gama, Alípio Jorge, Indre Zliobaite:
Guest editors introduction: special issue of the ECMLPKDD 2015 journal track. Data Min. Knowl. Discov. 29(5): 1113-1115 (2015) - [j59]Concha Bielza, Serafín Moral, Antonio Salmerón:
Recent Advances in Probabilistic Graphical Models. Int. J. Intell. Syst. 30(3): 207-208 (2015) - [j58]Gherardo Varando, Pedro L. López-Cruz, Thomas D. Nielsen, Pedro Larrañaga, Concha Bielza:
Conditional Density Approximations with Mixtures of Polynomials. Int. J. Intell. Syst. 30(3): 236-264 (2015) - [j57]Gherardo Varando, Concha Bielza, Pedro Larrañaga:
Decision boundary for discrete Bayesian network classifiers. J. Mach. Learn. Res. 16: 2725-2749 (2015) - [j56]Concha Bielza, João Gama, Alípio Jorge, Indre Zliobaite:
Guest Editors introduction: special issue of the ECMLPKDD 2015 journal track. Mach. Learn. 100(2-3): 157-159 (2015) - [j55]Bojan Mihaljevic, Ruth Benavides-Piccione, Concha Bielza, Javier DeFelipe, Pedro Larrañaga:
Bayesian Network Classifiers for Categorizing Cortical GABAergic Interneurons. Neuroinformatics 13(2): 193-208 (2015) - [j54]Pedro L. López-Cruz, Concha Bielza, Pedro Larrañaga:
Directional naive Bayes classifiers. Pattern Anal. Appl. 18(2): 225-246 (2015) - [j53]Hanen Borchani, Gherardo Varando, Concha Bielza, Pedro Larrañaga:
A survey on multi-output regression. WIREs Data Mining Knowl. Discov. 5(5): 216-233 (2015) - [c33]Luis Rodriguez-Lujan, Concha Bielza, Pedro Larrañaga:
Regularized Multivariate von Mises Distribution. CAEPIA 2015: 25-35 - [c32]Irene Córdoba-Sánchez, Concha Bielza, Pedro Larrañaga:
Towards Gaussian Bayesian Network Fusion. ECSQARU 2015: 519-528 - [c31]Javier Díaz, Concha Bielza, Jose L. Ocaña, Pedro Larrañaga:
Development of a Cyber-Physical System based on selective Gaussian naïve Bayes model for a self-predict laser surface heat treatment process control. ML4CPS 2015: 1-8 - 2014
- [j52]Concha Bielza, Pedro Larrañaga:
Discrete Bayesian Network Classifiers: A Survey. ACM Comput. Surv. 47(1): 5:1-5:43 (2014) - [j51]Luis Guerra, Concha Bielza, Víctor Robles, Pedro Larrañaga:
Semi-supervised projected model-based clustering. Data Min. Knowl. Discov. 28(4): 882-917 (2014) - [j50]Concha Bielza, Pedro Larrañaga:
Bayesian networks in neuroscience: a survey. Frontiers Comput. Neurosci. 8: 131 (2014) - [j49]Bojan Mihaljevic, Concha Bielza, Ruth Benavides-Piccione, Javier DeFelipe, Pedro Larrañaga:
Multi-dimensional classification of GABAergic interneurons with Bayesian network-modeled label uncertainty. Frontiers Comput. Neurosci. 8: 150 (2014) - [j48]Pedro L. López-Cruz, Pedro Larrañaga, Javier DeFelipe, Concha Bielza:
Bayesian network modeling of the consensus between experts: An application to neuron classification. Int. J. Approx. Reason. 55(1): 3-22 (2014) - [j47]Pedro L. López-Cruz, Concha Bielza, Pedro Larrañaga:
Learning mixtures of polynomials of multidimensional probability densities from data using B-spline interpolation. Int. J. Approx. Reason. 55(4): 989-1010 (2014) - [j46]Alfonso Ibáñez, Concha Bielza, Pedro Larrañaga:
Cost-sensitive selective naive Bayes classifiers for predicting the increase of the h-index for scientific journals. Neurocomputing 135: 42-52 (2014) - [j45]Luis Enrique Sucar, Concha Bielza, Eduardo F. Morales, Pablo Hernandez-Leal, Julio H. Zaragoza, Pedro Larrañaga:
Multi-label classification with Bayesian network-based chain classifiers. Pattern Recognit. Lett. 41: 14-22 (2014) - [j44]Hossein Karshenas, Roberto Santana, Concha Bielza, Pedro Larrañaga:
Multiobjective Estimation of Distribution Algorithm Based on Joint Modeling of Objectives and Variables. IEEE Trans. Evol. Comput. 18(4): 519-542 (2014) - [j43]Jesse Read, Concha Bielza, Pedro Larrañaga:
Multi-Dimensional Classification with Super-Classes. IEEE Trans. Knowl. Data Eng. 26(7): 1720-1733 (2014) - [c30]Gherardo Varando, Concha Bielza, Pedro Larrañaga:
Expressive Power of Binary Relevance and Chain Classifiers Based on Bayesian Networks for Multi-label Classification. Probabilistic Graphical Models 2014: 519-534 - 2013
- [j42]Hanen Borchani, Concha Bielza, Carlos Toro, Pedro Larrañaga:
Predicting human immunodeficiency virus inhibitors using multi-dimensional Bayesian network classifiers. Artif. Intell. Medicine 57(3): 219-229 (2013) - [j41]Rubén Armañanzas, Concha Bielza, Kallol Ray Chaudhuri, Pablo Martínez-Martín, Pedro Larrañaga:
Unveiling relevant non-motor Parkinson's disease severity symptoms using a machine learning approach. Artif. Intell. Medicine 58(3): 195-202 (2013) - [j40]Hossein Karshenas, Roberto Santana, Concha Bielza, Pedro Larrañaga:
Regularized continuous estimation of distribution algorithms. Appl. Soft Comput. 13(5): 2412-2432 (2013) - [j39]Diego Vidaurre, Concha Bielza, Pedro Larrañaga:
Sparse regularized local regression. Comput. Stat. Data Anal. 62: 122-135 (2013) - [j38]Diego Vidaurre, Concha Bielza, Pedro Larrañaga:
An L1-Regularized naïVE Bayes-Inspired Classifier for Discarding Redundant and Irrelevant Predictors. Int. J. Artif. Intell. Tools 22(4) (2013) - [j37]Roberto Santana, Rubén Armañanzas, Concha Bielza, Pedro Larrañaga:
Network measures for information extraction in evolutionary algorithms. Int. J. Comput. Intell. Syst. 6(6): 1163-1188 (2013) - [j36]Diego Vidaurre, Concha Bielza, Pedro Larrañaga:
Classification of neural signals from sparse autoregressive features. Neurocomputing 111: 21-26 (2013) - [j35]Miguel García-Torres, Rubén Armañanzas, Concha Bielza, Pedro Larrañaga:
Comparison of metaheuristic strategies for peakbin selection in proteomic mass spectrometry data. Inf. Sci. 222: 229-246 (2013) - [j34]Pedro Larrañaga, Hossein Karshenas, Concha Bielza, Roberto Santana:
A review on evolutionary algorithms in Bayesian network learning and inference tasks. Inf. Sci. 233: 109-125 (2013) - [j33]Concha Bielza, Juan A. Fernández del Pozo, Pedro Larrañaga:
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. 28(4): 720-731 (2013) - [j32]Diego Vidaurre, Marcel A. J. van Gerven, Concha Bielza, Pedro Larrañaga, Tom Heskes:
Bayesian Sparse Partial Least Squares. Neural Comput. 25(12): 3318-3339 (2013) - [j31]Alfonso Ibáñez, Concha Bielza, Pedro Larrañaga:
Relationship among research collaboration, number of documents and number of citations: a case study in Spanish computer science production in 2000-2009. Scientometrics 95(2): 689-716 (2013) - [j30]Alfonso Ibáñez, Pedro Larrañaga, Concha Bielza:
Cluster methods for assessing research performance: exploring Spanish computer science. Scientometrics 97(3): 571-600 (2013) - [c29]Luis Guerra, Ruth Benavides-Piccione, Concha Bielza, Víctor Robles, Javier DeFelipe, Pedro Larrañaga:
Semi-supervised Projected Clustering for Classifying GABAergic Interneurons. AIME 2013: 156-165 - [c28]Pedro L. López-Cruz, Concha Bielza, Pedro Larrañaga:
Learning Conditional Linear Gaussian Classifiers with Probabilistic Class Labels. CAEPIA 2013: 139-148 - [c27]Bojan Mihaljevic, Pedro Larrañaga, Concha Bielza:
Augmented Semi-naive Bayes Classifier. CAEPIA 2013: 159-167 - [c26]Pedro L. López-Cruz, Thomas D. Nielsen, Concha Bielza, Pedro Larrañaga:
Learning Mixtures of Polynomials of Conditional Densities from Data. CAEPIA 2013: 363-372 - [c25]Pedro Larrañaga, Concha Bielza:
Bayesian networks to answer challenging neuroscience questions. CBMS 2013: 2 - [c24]Laura Anton-Sanchez, Concha Bielza, Pedro Larrañaga:
Towards optimal neuronal wiring through estimation of distribution algorithms. GECCO (Companion) 2013: 1647-1650 - [e1]Concha Bielza, Antonio Salmerón, Amparo Alonso-Betanzos, José Ignacio Hidalgo, Luis Martínez-López, Alicia Troncoso Lora, Emilio Corchado, Juan M. Corchado:
Advances in Artificial Intelligence - 15th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2013, Madrid, Spain, September 17-20, 2013. Proceedings. Lecture Notes in Computer Science 8109, Springer 2013, ISBN 978-3-642-40642-3 [contents] - 2012
- [j29]Roberto Santana, Concha Bielza, Pedro Larrañaga:
Regularized logistic regression and multiobjective variable selection for classifying MEG data. Biol. Cybern. 106(6-7): 389-405 (2012) - [j28]Rubén Armañanzas, Pedro Larrañaga, Concha Bielza:
Ensemble transcript interaction networks: A case study on Alzheimer's disease. Comput. Methods Programs Biomed. 108(1): 442-450 (2012) - [j27]Diego Vidaurre, Concha Bielza, Pedro Larrañaga:
Lazy lasso for local regression. Comput. Stat. 27(3): 531-550 (2012) - [j26]Pedro Larrañaga, Hossein Karshenas, Concha Bielza, Roberto Santana:
A review on probabilistic graphical models in evolutionary computation. J. Heuristics 18(5): 795-819 (2012) - [j25]Luis Guerra, Víctor Robles, Concha Bielza, Pedro Larrañaga:
A comparison of clustering quality indices using outliers and noise. Intell. Data Anal. 16(4): 703-715 (2012) - [j24]Hanen Borchani, Concha Bielza, Pablo Martínez-Martín, Pedro Larrañaga:
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 45(6): 1175-1184 (2012) - [j23]Diego Vidaurre, Concha Bielza, Pedro Larrañaga:
Forward stagewise naïve Bayes. Prog. Artif. Intell. 1(1): 57-69 (2012) - [c23]Roberto Santana, Concha Bielza, Pedro Larrañaga:
Maximizing the number of polychronous groups in spiking networks. GECCO (Companion) 2012: 1499-1500 - 2011
- [j22]Juan A. Fernández del Pozo, Concha Bielza:
Dealing with complex queries in decision-support systems. Data Knowl. Eng. 70(2): 167-181 (2011) - [j21]Concha Bielza, Víctor Robles, Pedro Larrañaga:
Regularized logistic regression without a penalty term: An application to cancer classification with microarray data. Expert Syst. Appl. 38(5): 5110-5118 (2011) - [j20]Endika Bengoetxea, Pedro Larrañaga, Concha Bielza, Juan A. Fernández del Pozo:
Optimal row and column ordering to improve table interpretation using estimation of distribution algorithms. J. Heuristics 17(5): 567-588 (2011) - [j19]Hanen Borchani, Pedro Larrañaga, Concha Bielza:
Classifying evolving data streams with partially labeled data. Intell. Data Anal. 15(5): 655-670 (2011) - [j18]Concha Bielza, Guangdi Li, Pedro Larrañaga:
Multi-dimensional classification with Bayesian networks. Int. J. Approx. Reason. 52(6): 705-727 (2011) - [j17]Roberto Santana, Concha Bielza, Pedro Larrañaga:
Optimizing Brain Networks Topologies Using Multi-objective Evolutionary Computation. Neuroinformatics 9(1): 3-19 (2011) - [j16]Pedro L. López-Cruz, Concha Bielza, Pedro Larrañaga, Ruth Benavides-Piccione, Javier DeFelipe:
Models and Simulation of 3D Neuronal Dendritic Trees Using Bayesian Networks. Neuroinformatics 9(4): 347-369 (2011) - [j15]Alfonso Ibáñez, Pedro Larrañaga, Concha Bielza:
Using Bayesian networks to discover relationships between bibliometric indices. A case study of computer science and artificial intelligence journals. Scientometrics 89(2): 523-551 (2011) - [j14]Rubén Armañanzas, Yvan Saeys, Iñaki Inza, Miguel García-Torres, Concha Bielza, Yves Van de Peer, Pedro Larrañaga:
Peakbin Selection in Mass Spectrometry Data Using a Consensus Approach with Estimation of Distribution Algorithms. IEEE ACM Trans. Comput. Biol. Bioinform. 8(3): 760-774 (2011) - [c22]Pedro L. López-Cruz, Concha Bielza, Pedro Larrañaga:
The von Mises Naive Bayes Classifier for Angular Data. CAEPIA 2011: 145-154 - [c21]Hossein Karshenas, Roberto Santana, Concha Bielza, Pedro Larrañaga:
Multi-objective Optimization with Joint Probabilistic Modeling of Objectives and Variables. EMO 2011: 298-312 - [c20]Roberto Santana, Hossein Karshenas, Concha Bielza, Pedro Larrañaga:
Quantitative genetics in multi-objective optimization algorithms: from useful insights to effective methods. GECCO (Companion) 2011: 91-92 - [c19]Roberto Santana, Concha Bielza, Pedro Larrañaga:
Affinity propagation enhanced by estimation of distribution algorithms. GECCO 2011: 331-338 - [c18]Roberto Santana, Hossein Karshenas, Concha Bielza, Pedro Larrañaga:
Regularized k-order markov models in EDAs. GECCO 2011: 593-600 - [c17]Julio H. Zaragoza, Luis Enrique Sucar, Eduardo F. Morales, Concha Bielza, Pedro Larrañaga:
Bayesian Chain Classifiers for Multidimensional Classification. IJCAI 2011: 2192-2197 - [c16]Alfonso Ibáñez, Pedro Larrañaga, Concha Bielza:
Predicting the h-index with cost-sensitive naive Bayes. ISDA 2011: 599-604 - 2010
- [j13]Concha Bielza, Manuel Gómez, Prakash P. Shenoy:
Modeling challenges with influence diagrams: Constructing probability and utility models. Decis. Support Syst. 49(4): 354-364 (2010) - [j12]Concha Bielza, Juan A. Fernández del Pozo, Pedro Larrañaga, Endika Bengoetxea:
Multidimensional statistical analysis of the parameterization of a genetic algorithm for the optimal ordering of tables. Expert Syst. Appl. 37(1): 804-815 (2010) - [j11]Diego Vidaurre, Concha Bielza, Pedro Larrañaga:
Learning an L1-Regularized Gaussian Bayesian Network in the Equivalence Class Space. IEEE Trans. Syst. Man Cybern. Part B 40(5): 1231-1242 (2010) - [c15]Alfredo Cuesta-Infante, Roberto Santana, José Ignacio Hidalgo, Concha Bielza, Pedro Larrañaga:
Bivariate empirical and n-variate Archimedean copulas in estimation of distribution algorithms. IEEE Congress on Evolutionary Computation 2010: 1-8 - [c14]Roberto Santana, Concha Bielza, Pedro Larrañaga:
Using Probabilistic Dependencies Improves the Search of Conductance-Based Compartmental Neuron Models. EvoBIO 2010: 170-181 - [c13]Roberto Santana, Concha Bielza, Pedro Larrañaga:
Synergies between Network-Based Representation and Probabilistic Graphical Models for Classification, Inference and Optimization Problems in Neuroscience. IEA/AIE (3) 2010: 149-158 - [c12]Hanen Borchani, Pedro Larrañaga, Concha Bielza:
Mining Concept-Drifting Data Streams Containing Labeled and Unlabeled Instances. IEA/AIE (1) 2010: 531-540
2000 – 2009
- 2009
- [j10]Alfonso Ibáñez, Pedro Larrañaga, Concha Bielza:
Predicting citation count of Bioinformatics papers within four years of publication. Bioinform. 25(24): 3303-3309 (2009) - [j9]Maritza Correa, Concha Bielza, J. Pamies-Teixeira:
Comparison of Bayesian networks and artificial neural networks for quality detection in a machining process. Expert Syst. Appl. 36(3): 7270-7279 (2009) - [c11]Roberto Santana, Concha Bielza, José Antonio Lozano, Pedro Larrañaga:
Mining probabilistic models learned by EDAs in the optimization of multi-objective problems. GECCO 2009: 445-452 - [c10]Elva Díaz, Eunice Ponce de León, Pedro Larrañaga, Concha Bielza:
Probabilistic Graphical Markov Model Learning: An Adaptive Strategy. MICAI 2009: 225-236 - 2008
- [j8]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:
A review of estimation of distribution algorithms in bioinformatics. BioData Min. 1 (2008) - [j7]Concha Bielza, Juan A. Fernández del Pozo, Peter J. F. Lucas:
Explaining clinical decisions by extracting regularity patterns. Decis. Support Syst. 44(2): 397-408 (2008) - [j6]Maritza Correa, Concha Bielza, M. de J. Ramirez, José R. Alique:
A Bayesian network model for surface roughness prediction in the machining process. Int. J. Syst. Sci. 39(12): 1181-1192 (2008) - 2006
- [j5]Pedro Larrañaga, Borja Calvo, Roberto Santana, Concha Bielza, Josu Galdiano, Iñaki Inza, José Antonio Lozano, Rubén Armañanzas, Guzmán Santafé, Aritz Pérez Martínez, Victor Robles:
Machine learning in bioinformatics. Briefings Bioinform. 7(1): 86-112 (2006) - [j4]Enrique Ballestero, Concha Bielza, David Pla-Santamaria:
A decision approach to competitive electronic sealed-bid auctions for land. J. Oper. Res. Soc. 57(9): 1126-1133 (2006) - 2005
- [j3]Juan A. Fernández del Pozo, Concha Bielza, Manuel Gómez:
A list-based compact representation for large decision tables management. Eur. J. Oper. Res. 160(3): 638-662 (2005) - 2004
- [j2]Manuel Gómez, Concha Bielza:
Node deletion sequences in influence diagrams using genetic algorithms. Stat. Comput. 14(3): 181-198 (2004) - 2003
- [c9]Concha Bielza, Juan A. Fernández del Pozo, Peter J. F. Lucas:
Finding and Explaining Optimal Treatments. AIME 2003: 299-303 - [c8]Concha Bielza, Juan A. Fernández del Pozo, Peter J. F. Lucas:
Optimal Decision Explanation by Extracting Regularity Patterns. SGAI Conf. 2003: 283-294 - 2002
- [c7]Juan A. Fernández del Pozo, Concha Bielza:
An Interactive Framework for Open Queries in Decision Support Systems. IBERAMIA 2002: 254-264 - [c6]Juan A. Fernández del Pozo, Concha Bielza:
New Structures for Conditional Probability Tables. Probabilistic Graphical Models 2002 - [c5]Roberto O. Puch, Jim Q. Smith, Concha Bielza:
Inferentially Efficient Propagation in Non-Decomposable Bayesian Network with Hierarchical Junction Trees. Probabilistic Graphical Models 2002 - 2001
- [c4]Juan A. Fernández del Pozo, Concha Bielza, Manuel Gómez:
Knowledge Organisation in a Neonatal Jaundice Decision Support System. ISMDA 2001: 88-94 - 2000
- [j1]Concha Bielza, Manuel Gómez, Sixto Ríos-Insua, Juan A. Fernández del Pozo:
Structural, elicitation and computational issues faced when solving complex decision making problems with influence diagrams. Comput. Oper. Res. 27(7-8): 725-740 (2000)
1990 – 1999
- 1999
- [c3]Concha Bielza, Sixto Ríos-Insua, Manuel Gómez:
Influence Diagrams for Neonatal Jaundice Management. AIMDM 1999: 138-142 - 1997
- [c2]Concha Bielza, Peter Müller, David Ríos Insua:
Markov chain Monte Carlo methods for decision analysis. AISTATS 1997: 31-38 - [c1]Concha Bielza, Prakash P. Shenoy:
A Comparison of Decision Trees, Influence Diagrams and Valuation Networks for Asymmetric Decision Problems. AISTATS 1997: 39-46 - 1996
- [b1]Concepcion Bielza:
Contribuciones al análisis de problemas supercomplejos de toma de decisiones. Technical University of Madrid, Spain, 1996
Coauthor Index
[j110] [j109] [j108] [j107] [j106] [j105] [j104] [j103] [j102] [j101] [j100] [c57] [c56] [c55] [i10] [i9] [j99] [j98] [j97] [j96] [j95] [j94] [j93] [c54] [c53] [c52] [c51] [d1] [i8] [j92] [j91] [j90] [j89] [j88] [j87] [c50] [c49] [c48] [i7] [j86] [j85] [j84] [j83] [c47] [i6] [i5] [j82] [j81] [j80] [j79] [j78] [j77] [j76] [j75] [j74] [j73] [j72] [j71] [c46] [c45] [c44] [c43] [c42] [c41] [c40] [i4] [i3] [i2] [j70] [j69] [j68] [c39] [j67] [j66] [j65] [j64] [j63] [c38] [c37] [c36] [c35] [c34] [i1] [j62] [j61] [j58] [j57] [j55] [j54] [j53] [c33] [c32] [c31] [j52] [j51] [j50] [j49] [j48] [j47] [j46] [j45] [j44] [j43] [c30] [j42] [j41] [j40] [j39] [j38] [j37] [j36] [j35] [j34] [j33] [j32] [j31] [j30] [c29] [c28] [c27] [c26] [c25] [c24] [j29] [j28] [j27] [j26] [j25] [j24] [j23] [c23] [j21] [j20] [j19] [j18] [j17] [j16] [j15] [j14] [c22] [c21] [c20] [c19] [c18] [c17] [c16] [j12] [j11] [c15] [c14] [c13] [c12] [j10] [c11] [c10] [j8] [j5]
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