Vanessa Gómez-Verdejo

发表

Low-cost model selection for SVMs using local features

Miguel Lázaro-Gredilla, Vanessa Gómez-Verdejo, Emilio Parrado-Hernández, 2012, Eng. Appl. Artif. Intell..

Automatic Design of Neuromarkers for OCD Characterization

Manel Martínez-Ramón, Vanessa Gómez-Verdejo, Emilio Parrado-Hernández, 2014, ECML/PKDD.

Fast Classification with Neural Networks via Confidence Rating

Aníbal R. Figueiras-Vidal, Vanessa Gómez-Verdejo, Jerónimo Arenas-García, 2005, IWANN.

Evaluation of dimensionality reduction methods applied to numerical weather models for solar radiation forecasting

Sancho Salcedo-Sanz, Silvia Jiménez-Fernández, Manel Martínez-Ramón, 2018, Eng. Appl. Artif. Intell..

A conditional one-output likelihood formulation for multitask Gaussian processes pdf

Manel Martínez-Ramón, Vanessa Gómez-Verdejo, Óscar García Hinde, 2020, Neurocomputing.

Regularized Bagged Canonical Component Analysis for Multiclass Learning in Brain Imaging

Jussi Tohka, Vanessa Gómez-Verdejo, Carlos Sevilla-Salcedo, 2019, bioRxiv.

Nonnegative OPLS for Supervised Design of Filter Banks: Application to Image and Audio Feature Extraction

Vanessa Gómez-Verdejo, Sergio Muñoz-Romero, Jerónimo Arenas-García, 2018, IEEE Transactions on Multimedia.

Adaptive One-Class Support Vector Machine

Miguel Lázaro-Gredilla, Vanessa Gómez-Verdejo, Jerónimo Arenas-García, 2011, IEEE Transactions on Signal Processing.

Feature selection in solar radiation prediction using bootstrapped SVRs

Sancho Salcedo-Sanz, Silvia Jiménez-Fernández, Manel Martínez-Ramón, 2016, 2016 IEEE Congress on Evolutionary Computation (CEC).

A new boosting design of Support Vector Machine classifiers

Aníbal R. Figueiras-Vidal, Vanessa Gómez-Verdejo, Efraín Mayhua-López, 2015, Inf. Fusion.

Information-Theoretic Feature Selection for the Classification of Hysteresis Curves

Michel Verleysen, Vanessa Gómez-Verdejo, Jérôme Fleury, 2007, IWANN.

Identification of OCD-Relevant Brain Areas through Multivariate Feature Selection

Manel Martínez-Ramón, Vanessa Gómez-Verdejo, Emilio Parrado-Hernández, 2011, MLINI.

fMRI brain mapping with kernels

Manel Martínez-Ramón, Vanessa Gómez-Verdejo, Antonio Oliviero, 2012, 2012 3rd International Workshop on Cognitive Information Processing (CIP).

A novel framework for parsimonious multivariate analysis

Vanessa Gómez-Verdejo, Emilio Parrado-Hernández, Sergio Muñoz-Romero, 2017, Pattern Recognit..

Sparse and kernel OPLS feature extraction based on eigenvalue problem solving

Vanessa Gómez-Verdejo, Jerónimo Arenas-García, Sergio Muñoz-Romero, 2015, Pattern Recognit..

Committees of Adaboost ensembles with modified emphasis functions

Aníbal R. Figueiras-Vidal, Vanessa Gómez-Verdejo, Jerónimo Arenas-García, 2010, Neurocomputing.

Boosting by weighting critical and erroneous samples

Aníbal R. Figueiras-Vidal, Vanessa Gómez-Verdejo, Jerónimo Arenas-García, 2006, Neurocomputing.

Real AdaBoost With Gate Controlled Fusion

Aníbal R. Figueiras-Vidal, Vanessa Gómez-Verdejo, Efraín Mayhua-López, 2012, IEEE Transactions on Neural Networks and Learning Systems.

UC3M High Level Feature Extraction at TRECVID 2008

Manel Martínez-Ramón, Vanessa Gómez-Verdejo, Jerónimo Arenas-García, 2008, TRECVID.

Boosting by weighting boundary and erroneous samples

Aníbal R. Figueiras-Vidal, Vanessa Gómez-Verdejo, Jerónimo Arenas-García, 2005, ESANN.

An On-line Fisher Discriminant

Aníbal R. Figueiras-Vidal, Vanessa Gómez-Verdejo, Jerónimo Arenas-García, 2005, ESANN.

A Dynamically Adjusted Mixed Emphasis Method for Building Boosting Ensembles

Aníbal R. Figueiras-Vidal, Vanessa Gómez-Verdejo, Jerónimo Arenas-García, 2008, IEEE Transactions on Neural Networks.

Separate-variable adaptive combination of LMS adaptive filters for plant identification

Aníbal R. Figueiras-Vidal, Manel Martínez-Ramón, Vanessa Gómez-Verdejo, 2003, 2003 IEEE XIII Workshop on Neural Networks for Signal Processing (IEEE Cat. No.03TH8718).

Forecast-informed power load profiling: A novel approach

Manel Martínez-Ramón, Vanessa Gómez-Verdejo, Óscar García Hinde, 2020, Eng. Appl. Artif. Intell..

UC3M AT TRECVID 2010 Semantic Indexing Task

Vanessa Gómez-Verdejo, Jerónimo Arenas-García, Fernando Díaz-de-María, 2010, TRECVID.

Data Selection for Short Term load forecasting pdf

Manel Martínez-Ramón, Vanessa Gómez-Verdejo, Nestor Pereira, 2019, ArXiv.

Iterative orthonormalized partial least squares with sparsity constraints

Vanessa Gómez-Verdejo, Jerónimo Arenas-García, Sergio Muñoz-Romero, 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.

Information-theoretic feature selection for functional data classification

Michel Verleysen, Vanessa Gómez-Verdejo, Jérôme Fleury, 2009, Neurocomputing.

Comparison of feature representations in MRI-based MCI-to-AD conversion prediction

Vanessa Gómez-Verdejo, Jussi Tohka, Marta Gomez-Sancho, 2017, bioRxiv.

Discovering brain regions relevant to obsessive-compulsive disorder identification through bagging and transduction

John Shawe-Taylor, Manel Martínez-Ramón, Vanessa Gómez-Verdejo, 2014, Medical Image Anal..

Designing neural network committees by combining boosting ensembles

Aníbal R. Figueiras-Vidal, Vanessa Gómez-Verdejo, 2006, ESANN.

Corpus Viewer: NLP and ML-based Platform for Public Policy Making and Implementation

Doaa Samy, Vanessa Gómez-Verdejo, Jerónimo Arenas-García, 2019, Proces. del Leng. Natural.

Voxel Selection in MRI through Bagging and Conformal Analysis: Application to Detection of Obsessive Compulsive Disorder

John Shawe-Taylor, Manel Martínez-Ramón, Vanessa Gómez-Verdejo, 2012, 2012 Second International Workshop on Pattern Recognition in NeuroImaging.

Sign-Consistency Based Variable Importance for Machine Learning in Brain Imaging

Jussi Tohka, Vanessa Gómez-Verdejo, Emilio Parrado-Hernández, 2017, Neuroinformatics.

A multiple kernel learning approach to perform classification of groups from complex-valued fMRI data analysis: Application to schizophrenia

Vince D. Calhoun, Kent A. Kiehl, Manel Martínez-Ramón, 2014, NeuroImage.

Fast evaluation of neural networks via confidence rating

Aníbal R. Figueiras-Vidal, Vanessa Gómez-Verdejo, Jerónimo Arenas-García, 2007, Neurocomputing.

Real Adaboost Ensembles with Emphasized Subsampling

Vanessa Gómez-Verdejo, Jerónimo Arenas-García, Sergio Muñoz-Romero, 2009, IWANN.

New algorithms for improved adaptive convex combination of LMS transversal filters

Aníbal R. Figueiras-Vidal, Vanessa Gómez-Verdejo, Jerónimo Arenas-García, 2005, IEEE Transactions on Instrumentation and Measurement.

Sign-consistency based variable importance for machine learning in brain imaging

Vanessa Gómez-Verdejo, Emilio Parrado-Hernández, Jussi Tohka, 2017 .

Analysis of fMRI time series with mutual information

Manel Martínez-Ramón, Vanessa Gómez-Verdejo, Antonio Oliviero, 2012, Medical Image Anal..

Improving boosting performance with a local combination of learners

Aníbal R. Figueiras-Vidal, Vanessa Gómez-Verdejo, Efraín Mayhua-López, 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).

Voxel importance in classifier ensembles based on sign consistency patterns: application to sMRI

Vanessa Gómez-Verdejo, Jussi Tohka, V. Gómez-Verdejo, 2016, 2016 International Workshop on Pattern Recognition in Neuroimaging (PRNI).

Support Vector Machines With Constraints for Sparsity in the Primal Parameters

Miguel Lázaro-Gredilla, Vanessa Gómez-Verdejo, Jerónimo Arenas-García, 2011, IEEE Transactions on Neural Networks.

Regularized Multivariate Analysis Framework for Interpretable High-Dimensional Variable Selection

Vanessa Gómez-Verdejo, Jerónimo Arenas-García, Sergio Muñoz-Romero, 2016, IEEE Computational Intelligence Magazine.

Comparison of feature representations in MRI-based MCI-to-AD conversion prediction

Jussi Tohka, Vanessa Gómez-Verdejo, Marta Gómez-Sancho, 2017, bioRxiv.