2025
Teacher privileged distillation: How to deal with imperfect teachers?
Knowl. Based Syst., 2025
Extending the learning using privileged information paradigm to logistic regression.
Neurocomputing, 2025
2024
Continuous estimation of distribution algorithms for the parametric optimization of geothermal power plants.
Proceedings of the 7th International Conference on Computational Intelligence and Intelligent Systems, 2024
2023
SNDProb: A Probabilistic Approach for Streaming Novelty Detection.
IEEE Trans. Knowl. Data Eng., June, 2023
Evolved Neural Networks for Building Energy Prediction.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2023
2022
Vibration Analysis for Rotatory Elements Wear Detection in Paper Mill Machine.
Proceedings of the Database and Expert Systems Applications - DEXA 2022 Workshops, 2022
Learning a Battery of COVID-19 Mortality Prediction Models by Multi-objective Optimization.
Proceedings of the Artificial Intelligence in Medicine, 2022
2020
Analyzing rare event, anomaly, novelty and outlier detection terms under the supervised classification framework.
Artif. Intell. Rev., 2020
Using Convolutional Neural Network for Chest X-ray Image classification.
Proceedings of the 43rd International Convention on Information, 2020
2019
A Note on the Behavior of Majority Voting in Multi-Class Domains with Biased Annotators.
IEEE Trans. Knowl. Data Eng., 2019
Aggregated outputs by linear models: An application on marine litter beaching prediction.
Inf. Sci., 2019
2018
A system for airport weather forecasting based on circular regression trees.
Environ. Model. Softw., 2018
Learning to classify software defects from crowds: A novel approach.
Appl. Soft Comput., 2018
2017
Measuring the class-imbalance extent of multi-class problems.
Pattern Recognit. Lett., 2017
Learning from Proportions of Positive and Unlabeled Examples.
Int. J. Intell. Syst., 2017
2016
Semisupervised Multiclass Classification Problems With Scarcity of Labeled Data: A Theoretical Study.
IEEE Trans. Neural Networks Learn. Syst., 2016
Weak supervision and other non-standard classification problems: A taxonomy.
Pattern Recognit. Lett., 2016
Efficient approximation of probability distributions with k-order decomposable models.
Int. J. Approx. Reason., 2016
2015
Multidimensional Learning from Crowds: Usefulness and Application of Expertise Detection.
Int. J. Intell. Syst., 2015
Evaluating machine-learning techniques for recruitment forecasting of seven North East Atlantic fish species.
Ecol. Informatics, 2015
Dealing with the evaluation of supervised classification algorithms.
Artif. Intell. Rev., 2015
A Novel Weakly Supervised Problem: Learning from Positive-Unlabeled Proportions.
Proceedings of the Advances in Artificial Intelligence, 2015
2014
Assisting in search heuristics selection through multidimensional supervised classification: A case study on software testing.
Inf. Sci., 2014
2013
Learning Bayesian network classifiers from label proportions.
Pattern Recognit., 2013
Supervised pre-processing approaches in multiple class variables classification for fish recruitment forecasting.
Environ. Model. Softw., 2013
A new measure for gene expression biclustering based on non-parametric correlation.
Comput. Methods Programs Biomed., 2013
Multidimensional k-Interaction Classifier: Taking Advantage of All the Information Contained in Low Order Interactions.
Proceedings of the Advances in Artificial Intelligence, 2013
Learning from Crowds in Multi-dimensional Classification Domains.
Proceedings of the Advances in Artificial Intelligence, 2013
2012
Wrapper positive Bayesian network classifiers.
Knowl. Inf. Syst., 2012
Approaching Sentiment Analysis by using semi-supervised learning of multi-dimensional classifiers.
Neurocomputing, 2012
2011
Peakbin Selection in Mass Spectrometry Data Using a Consensus Approach with Estimation of Distribution Algorithms.
IEEE ACM Trans. Comput. Biol. Bioinform., 2011
Learning Naive Bayes Models for Multiple-Instance Learning with Label Proportions.
Proceedings of the Advances in Artificial Intelligence, 2011
2009
Microarray Analysis of Autoimmune Diseases by Machine Learning Procedures.
IEEE Trans. Inf. Technol. Biomed., 2009
Bayesian classifiers based on kernel density estimation: Flexible classifiers.
Int. J. Approx. Reason., 2009
2008
Proceedings of the Third Workshop on New Challenges for Feature Selection in Data Mining and Knowledge Discovery, 2008
Detecting reliable gene interactions by a hierarchy of Bayesian network classifiers.
Comput. Methods Programs Biomed., 2008
A review of estimation of distribution algorithms in bioinformatics.
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BioData Min., 2008
2007
Wrapper discretization by means of estimation of distribution algorithms.
Intell. Data Anal., 2007
A review of feature selection techniques in bioinformatics.
Bioinform., 2007
2006
Supervised classification with conditional Gaussian networks: Increasing the structure complexity from naive Bayes.
Int. J. Approx. Reason., 2006
Machine learning in bioinformatics.
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Briefings Bioinform., 2006
Information Theory and Classification Error in Probabilistic Classifiers.
Proceedings of the Discovery Science, 9th International Conference, 2006
2005
Feature selection in Bayesian classifiers for the prognosis of survival of cirrhotic patients treated with TIPS.
J. Biomed. Informatics, 2005
A Guide to the Literature on Inferring Genetic Networks by Probabilistic Graphical Models.
Proceedings of the Data Analysis and Visualization in Genomics and Proteomics, 2005
2004
Gene Selection For Cancer Classification Using Wrapper Approaches.
Int. J. Pattern Recognit. Artif. Intell., 2004
Filter versus wrapper gene selection approaches in DNA microarray domains.
Artif. Intell. Medicine, 2004
Selective Classifiers Can Be Too Restrictive: A Case-Study in Oesophageal Cancer.
Proceedings of the Biological and Medical Data Analysis, 5th International Symposium, 2004
2003
Learning Bayesian networks in the space of structures by estimation of distribution algorithms.
Int. J. Intell. Syst., 2003
2002
Gene selection by sequential search wrapper approaches in microarray cancer class prediction.
J. Intell. Fuzzy Syst., 2002
Floating Search Methods in Learning Bayesian Networks.
Proceedings of the First European Workshop on Probabilistic Graphical Models, 6-8 November - 2002, 2002
Rule Induction by Estimation of Distribution Algorithms.
Proceedings of the Estimation of Distribution Algorithms, 2002
Feature Weighting for Nearest Neighbor by Estimation of Distribution Algorithms.
Proceedings of the Estimation of Distribution Algorithms, 2002
Feature Subset Selection by Estimation of Distribution Algorithms.
Proceedings of the Estimation of Distribution Algorithms, 2002
2001
Dimensionality Reduction in Unsupervised Learning of Conditional Gaussian Networks.
IEEE Trans. Pattern Anal. Mach. Intell., 2001
Feature subset selection by Bayesian networks: a comparison with genetic and sequential algorithms.
Int. J. Approx. Reason., 2001
Using Bayesian networks in the construction of a bi-level multi-classifier. A case study using intensive care unit patients data.
Artif. Intell. Medicine, 2001
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, 2001
On Applying Supervised Classification Techniques in Medicine.
Proceedings of the Medical Data Analysis, Second International Symposium, 2001
Prototype Selection and Feature Subset Selection by Estimation of Distribution Algorithms. A Case Study in the Survival of Cirrhotic Patients Treated with TIPS.
Proceedings of the Artificial Intelligence Medicine, 2001
2000
Feature Subset Selection by Bayesian network-based optimization.
Artif. Intell., 2000
Proceedings of the Medical Data Analysis, First International Symposium, 2000
Feature Subset Selection Using Probabilistic Tree Structures. A Case Study in the Survival of Cirrhotic Patients Treated with TIPS.
Proceedings of the Medical Data Analysis, First International Symposium, 2000
1999
Representing the behaviour of supervised classification learning algorithms by Bayesian networks.
Pattern Recognit. Lett., 1999
Genetic Algorithms for the Travelling Salesman Problem: A Review of Representations and Operators.
Artif. Intell. Rev., 1999
Machine Learning Inspired Approaches to Combine Standard Medical Measures at an Intensive Care Unit.
Proceedings of the Artificial Intelligence in Medicine. Joint European Conference on Artificial Intelligence in Medicine and Medical Decision Making, 1999