Concha Bielza

According to our database1, Concha Bielza authored at least 123 papers between 1999 and 2019.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Other 

Links

Homepages:

On csauthors.net:

Bibliography

2019
Tractable learning of Bayesian networks from partially observed data.
Pattern Recognition, 2019

A circular-linear dependence measure under Johnson-Wehrly distributions and its application in Bayesian networks.
Inf. Sci., 2019

Circular Bayesian classifiers using wrapped Cauchy distributions.
Data Knowl. Eng., 2019

Learning tractable Bayesian networks in the space of elimination orders.
Artif. Intell., 2019

A Directional-Linear Bayesian Network and Its Application for Clustering and Simulation of Neural Somas.
IEEE Access, 2019

Random Forests for Regression as a Weighted Sum of ${k}$ -Potential Nearest Neighbors.
IEEE Access, 2019

2018
3D morphology-based clustering and simulation of human pyramidal cell dendritic spines.
PLoS Computational Biology, 2018

Clustering of Data Streams With Dynamic Gaussian Mixture Models: An IoT Application in Industrial Processes.
IEEE Internet of Things Journal, 2018

Tractability of most probable explanations in multidimensional Bayesian network classifiers.
Int. J. Approx. Reasoning, 2018

Towards a supervised classification of neocortical interneuron morphologies.
BMC Bioinformatics, 2018

Discrete model-based clustering with overlapping subsets of attributes.
Proceedings of the International Conference on Probabilistic Graphical Models, 2018

Learning Bayesian network classifiers with completed partially directed acyclic graphs.
Proceedings of the International Conference on Probabilistic Graphical Models, 2018

A partial orthogonalization method for simulating covariance and concentration graph matrices.
Proceedings of the International Conference on Probabilistic Graphical Models, 2018

Multi-dimensional Bayesian Network Classifier Trees.
Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2018, 2018

A Fast Metropolis-Hastings Method for Generating Random Correlation Matrices.
Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2018, 2018

Asymmetric Hidden Markov Models with Continuous Variables.
Proceedings of the Advances in Artificial Intelligence, 2018

Bayesian Optimization of the PC Algorithm for Learning Gaussian Bayesian Networks.
Proceedings of the Advances in Artificial Intelligence, 2018

2017
Univariate and bivariate truncated von Mises distributions.
Progress in AI, 2017

Frobenius Norm Regularization for the Multivariate Von Mises Distribution.
Int. J. Intell. Syst., 2017

Network design through forests with degree- and role-constrained minimum spanning trees.
J. Heuristics, 2017

Architecture for anomaly detection in a laser heating surface process.
Proceedings of the 22nd IEEE International Conference on Emerging Technologies and Factory Automation, 2017

2016
Learning Bayesian networks with low inference complexity.
Progress in AI, 2016

Dendritic and Axonal Wiring Optimization of Cortical GABAergic Interneurons.
Neuroinformatics, 2016

Genetic algorithms and Gaussian Bayesian networks to uncover the predictive core set of bibliometric indices.
JASIST, 2016

Decision functions for chain classifiers based on Bayesian networks for multi-label classification.
Int. J. Approx. Reasoning, 2016

Mining multi-dimensional concept-drifting data streams using Bayesian network classifiers.
Intell. Data Anal., 2016

Anomaly Detection with a Spatio-Temporal Tracking of the Laser Spot.
Proceedings of the STAIRS 2016, 2016

Learning Tractable Multidimensional Bayesian Network Classifiers.
Proceedings of the Probabilistic Graphical Models - Eighth International Conference, 2016

Dynamic Bayesian Network-Based Anomaly Detection for In-Process Visual Inspection of Laser Surface Heat Treatment.
Proceedings of the Machine Learning for Cyber Physical Systems, 2016

Hybrid Gaussian and von Mises Model-Based Clustering.
Proceedings of the ECAI 2016 - 22nd European Conference on Artificial Intelligence, 29 August-2 September 2016, The Hague, The Netherlands, 2016

Tree-Structured Bayesian Networks for Wrapped Cauchy Directional Distributions.
Proceedings of the Advances in Artificial Intelligence, 2016

2015
A survey on multi-output regression.
Wiley Interdiscip. Rev. Data Min. Knowl. Discov., 2015

Directional naive Bayes classifiers.
Pattern Anal. Appl., 2015

Bayesian Network Classifiers for Categorizing Cortical GABAergic Interneurons.
Neuroinformatics, 2015

Guest Editors introduction: special issue of the ECMLPKDD 2015 journal track.
Machine Learning, 2015

Decision boundary for discrete Bayesian network classifiers.
J. Mach. Learn. Res., 2015

Conditional Density Approximations with Mixtures of Polynomials.
Int. J. Intell. Syst., 2015

Recent Advances in Probabilistic Graphical Models.
Int. J. Intell. Syst., 2015

Guest editors introduction: special issue of the ECMLPKDD 2015 journal track.
Data Min. Knowl. Discov., 2015

Interval-based ranking in noisy evolutionary multi-objective optimization.
Comp. Opt. and Appl., 2015

Classifying GABAergic interneurons with semi-supervised projected model-based clustering.
Artificial Intelligence in Medicine, 2015

Development of a Cyber-Physical System based on selective Gaussian naïve Bayes model for a self-predict laser surface heat treatment process control.
Proceedings of the Machine Learning for Cyber Physical Systems, 2015

Towards Gaussian Bayesian Network Fusion.
Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2015

Regularized Multivariate von Mises Distribution.
Proceedings of the Advances in Artificial Intelligence, 2015

2014
Multi-Dimensional Classification with Super-Classes.
IEEE Trans. Knowl. Data Eng., 2014

Multiobjective Estimation of Distribution Algorithm Based on Joint Modeling of Objectives and Variables.
IEEE Trans. Evolutionary Computation, 2014

Multi-label classification with Bayesian network-based chain classifiers.
Pattern Recognition Letters, 2014

Cost-sensitive selective naive Bayes classifiers for predicting the increase of the h-index for scientific journals.
Neurocomputing, 2014

Bayesian network modeling of the consensus between experts: An application to neuron classification.
Int. J. Approx. Reasoning, 2014

Learning mixtures of polynomials of multidimensional probability densities from data using B-spline interpolation.
Int. J. Approx. Reasoning, 2014

Multi-dimensional classification of GABAergic interneurons with Bayesian network-modeled label uncertainty.
Front. Comput. Neurosci., 2014

Bayesian networks in neuroscience: a survey.
Front. Comput. Neurosci., 2014

Semi-supervised projected model-based clustering.
Data Min. Knowl. Discov., 2014

Discrete Bayesian Network Classifiers: A Survey.
ACM Comput. Surv., 2014

Expressive Power of Binary Relevance and Chain Classifiers Based on Bayesian Networks for Multi-label Classification.
Proceedings of the Probabilistic Graphical Models - 7th European Workshop, 2014

2013
Cluster methods for assessing research performance: exploring Spanish computer science.
Scientometrics, 2013

Relationship among research collaboration, number of documents and number of citations: a case study in Spanish computer science production in 2000-2009.
Scientometrics, 2013

Bayesian Sparse Partial Least Squares.
Neural Computation, 2013

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., 2013

A review on evolutionary algorithms in Bayesian network learning and inference tasks.
Inf. Sci., 2013

Comparison of metaheuristic strategies for peakbin selection in proteomic mass spectrometry data.
Inf. Sci., 2013

Classification of neural signals from sparse autoregressive features.
Neurocomputing, 2013

Network measures for information extraction in evolutionary algorithms.
Int. J. Comput. Intell. Syst., 2013

An L1-Regularized naïVE Bayes-Inspired Classifier for Discarding Redundant and Irrelevant Predictors.
International Journal on Artificial Intelligence Tools, 2013

Sparse regularized local regression.
Computational Statistics & Data Analysis, 2013

Regularized continuous estimation of distribution algorithms.
Appl. Soft Comput., 2013

Predicting human immunodeficiency virus inhibitors using multi-dimensional Bayesian network classifiers.
Artificial Intelligence in Medicine, 2013

Unveiling relevant non-motor Parkinson's disease severity symptoms using a machine learning approach.
Artificial Intelligence in Medicine, 2013

Towards optimal neuronal wiring through estimation of distribution algorithms.
Proceedings of the Genetic and Evolutionary Computation Conference, 2013

Bayesian networks to answer challenging neuroscience questions.
Proceedings of the 26th IEEE International Symposium on Computer-Based Medical Systems, 2013

Augmented Semi-naive Bayes Classifier.
Proceedings of the Advances in Artificial Intelligence, 2013

Learning Mixtures of Polynomials of Conditional Densities from Data.
Proceedings of the Advances in Artificial Intelligence, 2013

Learning Conditional Linear Gaussian Classifiers with Probabilistic Class Labels.
Proceedings of the Advances in Artificial Intelligence, 2013

Semi-supervised Projected Clustering for Classifying GABAergic Interneurons.
Proceedings of the Artificial Intelligence in Medicine, 2013

2012
Forward stagewise naïve Bayes.
Progress in AI, 2012

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).
Journal of Biomedical Informatics, 2012

A comparison of clustering quality indices using outliers and noise.
Intell. Data Anal., 2012

A review on probabilistic graphical models in evolutionary computation.
J. Heuristics, 2012

Ensemble transcript interaction networks: A case study on Alzheimer's disease.
Computer Methods and Programs in Biomedicine, 2012

Regularized logistic regression and multiobjective variable selection for classifying MEG data.
Biological Cybernetics, 2012

Maximizing the number of polychronous groups in spiking networks.
Proceedings of the Genetic and Evolutionary Computation Conference, 2012

2011
Peakbin Selection in Mass Spectrometry Data Using a Consensus Approach with Estimation of Distribution Algorithms.
IEEE/ACM Trans. Comput. Biology Bioinform., 2011

Using Bayesian networks to discover relationships between bibliometric indices. A case study of computer science and artificial intelligence journals.
Scientometrics, 2011

Optimizing Brain Networks Topologies Using Multi-objective Evolutionary Computation.
Neuroinformatics, 2011

Models and Simulation of 3D Neuronal Dendritic Trees Using Bayesian Networks.
Neuroinformatics, 2011

Multi-dimensional classification with Bayesian networks.
Int. J. Approx. Reasoning, 2011

Classifying evolving data streams with partially labeled data.
Intell. Data Anal., 2011

Optimal row and column ordering to improve table interpretation using estimation of distribution algorithms.
J. Heuristics, 2011

Regularized logistic regression without a penalty term: An application to cancer classification with microarray data.
Expert Syst. Appl., 2011

Dealing with complex queries in decision-support systems.
Data Knowl. Eng., 2011

Predicting the h-index with cost-sensitive naive Bayes.
Proceedings of the 11th International Conference on Intelligent Systems Design and Applications, 2011

Bayesian Chain Classifiers for Multidimensional Classification.
Proceedings of the IJCAI 2011, 2011

Quantitative genetics in multi-objective optimization algorithms: from useful insights to effective methods.
Proceedings of the 13th Annual Genetic and Evolutionary Computation Conference, 2011

Regularized k-order markov models in EDAs.
Proceedings of the 13th Annual Genetic and Evolutionary Computation Conference, 2011

Affinity propagation enhanced by estimation of distribution algorithms.
Proceedings of the 13th Annual Genetic and Evolutionary Computation Conference, 2011

Multi-objective Optimization with Joint Probabilistic Modeling of Objectives and Variables.
Proceedings of the Evolutionary Multi-Criterion Optimization, 2011

The von Mises Naive Bayes Classifier for Angular Data.
Proceedings of the Advances in Artificial Intelligence, 2011

2010
Learning an L1-Regularized Gaussian Bayesian Network in the Equivalence Class Space.
IEEE Trans. Systems, Man, and Cybernetics, Part B, 2010

Multidimensional statistical analysis of the parameterization of a genetic algorithm for the optimal ordering of tables.
Expert Syst. Appl., 2010

Modeling challenges with influence diagrams: Constructing probability and utility models.
Decision Support Systems, 2010

Synergies between Network-Based Representation and Probabilistic Graphical Models for Classification, Inference and Optimization Problems in Neuroscience.
Proceedings of the Trends in Applied Intelligent Systems, 2010

Mining Concept-Drifting Data Streams Containing Labeled and Unlabeled Instances.
Proceedings of the Trends in Applied Intelligent Systems, 2010

Using Probabilistic Dependencies Improves the Search of Conductance-Based Compartmental Neuron Models.
Proceedings of the Evolutionary Computation, 2010

Bivariate empirical and n-variate Archimedean copulas in estimation of distribution algorithms.
Proceedings of the IEEE Congress on Evolutionary Computation, 2010

2009
Comparison of Bayesian networks and artificial neural networks for quality detection in a machining process.
Expert Syst. Appl., 2009

Predicting citation count of Bioinformatics papers within four years of publication.
Bioinformatics, 2009

Probabilistic Graphical Markov Model Learning: An Adaptive Strategy.
Proceedings of the MICAI 2009: Advances in Artificial Intelligence, 2009

Mining probabilistic models learned by EDAs in the optimization of multi-objective problems.
Proceedings of the Genetic and Evolutionary Computation Conference, 2009

2008
A Bayesian network model for surface roughness prediction in the machining process.
Int. J. Systems Science, 2008

Explaining clinical decisions by extracting regularity patterns.
Decision Support Systems, 2008

A review of estimation of distribution algorithms in bioinformatics.
BioData Mining, 2008

2006
A decision approach to competitive electronic sealed-bid auctions for land.
JORS, 2006

Machine learning in bioinformatics.
Briefings in Bioinformatics, 2006

2005
A list-based compact representation for large decision tables management.
European Journal of Operational Research, 2005

2004
Node deletion sequences in influence diagrams using genetic algorithms.
Statistics and Computing, 2004

2003
Optimal Decision Explanation by Extracting Regularity Patterns.
Proceedings of the Research and Development in Intelligent Systems XX, 2003

Finding and Explaining Optimal Treatments.
Proceedings of the Artificial Intelligence in Medicine, 2003

2002
Inferentially Efficient Propagation in Non-Decomposable Bayesian Network with Hierarchical Junction Trees.
Proceedings of the First European Workshop on Probabilistic Graphical Models, 6-8 November - 2002, 2002

New Structures for Conditional Probability Tables.
Proceedings of the First European Workshop on Probabilistic Graphical Models, 6-8 November - 2002, 2002

An Interactive Framework for Open Queries in Decision Support Systems.
Proceedings of the Advances in Artificial Intelligence, 2002

2001
Knowledge Organisation in a Neonatal Jaundice Decision Support System.
Proceedings of the Medical Data Analysis, Second International Symposium, 2001

2000
Structural, elicitation and computational issues faced when solving complex decision making problems with influence diagrams.
Computers & OR, 2000

1999
Influence Diagrams for Neonatal Jaundice Management.
Proceedings of the Artificial Intelligence in Medicine. Joint European Conference on Artificial Intelligence in Medicine and Medical Decision Making, 1999


  Loading...