sample of publications

• articles 

  • Bayesian sparse factor analysis with kernelized observations.  NEUROCOMPUTING.  490. 2022
  • A Novel Bayesian Linear Regression Model for the Analysis of Neuroimaging Data.  Applied Sciences (Bucarest).  12:2571-2588. 2022
  • Sparse semi-supervised heterogeneous interbattery bayesian analysis.  PATTERN RECOGNITION.  120:1-13. 2021
  • Forecast-informed power load profiling: A novel approach.  ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE.  96:1-12. 2020
  • Regularized bagged canonical component analysis for multiclass learning in brain imaging.  NEUROINFORMATICS.  18:641-659. 2020
  • Sign-consistency based variable importance for machine learning in brain imaging.  NEUROINFORMATICS.  17:593-609. 2019
  • Comparison of feature representations in MRI-based MCI-to-AD conversion prediction.  MAGNETIC RESONANCE IMAGING.  50:84-95. 2018
  • Nonnegative OPLS for supervised design of filter banks: application to image and audio feature extraction.  IEEE TRANSACTIONS ON MULTIMEDIA.  20:1751-1766. 2018
  • Evaluation of dimensionality reduction methods applied to numerical weather models for solar radiation forecasting.  ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE.  69:157-167. 2018
  • A novel framework for parsimonious multivariate analysis.  PATTERN RECOGNITION.  71:173-186. 2017
  • Regularized multivariate analysis framework for interpretable high-dimensional variable selection.  IEEE Computational Intelligence Magazine.  11:24-35. 2016
  • A new boosting design of Support Vector Machine classifiers.  Information Fusion.  25:63-71. 2015
  • Sparse and kernel OPLS feature extraction based on eigenvalue problem solving.  PATTERN RECOGNITION.  48:1797-1811. 2015
  • Discovering brain regions relevant to obsessive-compulsive disorder identification through bagging and transduction.  MEDICAL IMAGE ANALYSIS.  18:435-448. 2014
  • A multiple kernel learning approach to perform classification of groups from complex-valued fMRI data analysis: Application to schizophrenia.  NEUROIMAGE.  87:1-17. 2014
  • Real AdaBoost With Gate Controlled Fusion.  IEEE Transactions on Neural Networks and Learning Systems.  23:2003-2009. 2012
  • Low-cost model selection for SVMs using local features.  ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE.  25:1203-1211. 2012
  • Analysis of fMRI time series with mutual information.  MEDICAL IMAGE ANALYSIS.  16:451-458. 2012
  • Support Vector Machines with Constraints for Sparsity in the Primal Parameters.  IEEE TRANSACTIONS ON NEURAL NETWORKS.  22:1269-1283. 2011
  • Adaptive one-class support vector machine.  IEEE TRANSACTIONS ON SIGNAL PROCESSING.  59:2975-2981. 2011
  • Committees of Adaboost Ensembles with Modified Emphasis Functions.  NEUROCOMPUTING.  73:1289-1292. 2010
  • Information-Theoretic Feature Selection for Functional Data Classification.  NEUROCOMPUTING.  72:3580-3589. 2009
  • A Dynamically Adjusted Mixed Emphasis Method for Building Boosting Ensembles.  IEEE Transactions on Neural Networks and Learning Systems.  19:3-17. 2008

• conference contributions 

  • Corpus Viewer: NLP and ML-based Platform for Public Policy Making and Implementation.  193-196. 2019
  • Feature selection in solar radiation prediction using bootstrapped SVRs 2016
  • Voxel importance in classifier ensembles based on sign consistency patterns: application to sMRI 2016
  • Iterative orthonormalized partial least squares with sparsity constraints.  3387-3391. 2013
  • Voxel Selection in MRI Through Bagging and Conformal Analysis: Application to Detection of Obsessive Complusive Disorder 2012
  • UC3M High Level Feature Extraction at TRECVID 2008 2008