Verónica Bolón-Canedo

发表

A scalable saliency-based Feature selection method with instance level information

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, João Gama, 2019, Knowl. Based Syst..

Dealing with inter-expert variability in Retinopathy of Prematurity through machine learning

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Deniz Erdogmus, 2015 .

Combination of Outputs

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, A. Alonso-Betanzos, 2018 .

Selection of the Best Base Classifier in One-Versus-One Using Data Complexity Measures

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Laura Morán-Fernández, 2016, CAEPIA.

Feature and kernel learning

Verónica Bolón-Canedo, Fabio Aiolli, Michele Donini, 2015, ESANN.

ESANN 2011 19th European Symposium on Artificial Neural Networks

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Jose C. Principe, 2011 .

On the scalability of feature selection methods on high-dimensional data

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Bertha Guijarro-Berdiñas, 2017, Knowledge and Information Systems.

Feature selection for high-dimensional data

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, 2016, Progress in Artificial Intelligence.

Feature Selection for Big Visual Data: Overview and Challenges

Beatriz Remeseiro, Verónica Bolón-Canedo, Brais Cancela, 2018, ICIAR.

An ensemble of filters and classifiers for microarray data classification

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, 2012, Pattern Recognit..

On the effectiveness of discretization on gene selection of microarray data

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).

アンサンブル特徴選択:均一系および不均一系アプローチ【Powered by NICT】

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Iago Porto-Díaz, 2017 .

Applications of Ensembles Versus Traditional Approaches: Experimental Results

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, 2018 .

A combination of discretization and filter methods for improving classification performance in KDD Cup 99 dataset

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, 2009, 2009 International Joint Conference on Neural Networks.

Ensembles for Feature Selection

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, 2018 .

Feature Selection with Limited Bit Depth Mutual Information for Embedded Systems

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Laura Morán-Fernández, 2018 .

Centralized vs. distributed feature selection methods based on data complexity measures

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Laura Moran-Fernandez, 2017, Knowl. Based Syst..

Multithreaded and Spark parallelization of feature selection filters

Sabela Ramos, Verónica Bolón-Canedo, Amparo Alonso-Betanzos, 2016, J. Comput. Sci..

Feature Selection in DNA Microarray Classification

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, 2015 .

Feature selection in image analysis: a survey

Verónica Bolón-Canedo, Beatriz Remeseiro, Beatriz Remeseiro, 2019, Artificial Intelligence Review.

Scalability Analysis of ANN Training Algorithms with Feature Selection

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Bertha Guijarro-Berdiñas, 2011, CAEPIA.

Up-to-Date Feature Selection Methods for Scalable and Efficient Machine Learning

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, 2013 .

A Time Efficient Approach for Distributed Feature Selection Partitioning by Features

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Laura Moran-Fernandez, 2015, CAEPIA.

Ensemble feature selection: Homogeneous and heterogeneous approaches

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Iago Porto-Díaz, 2017, Knowl. Based Syst..

Parallel feature selection for distributed-memory clusters

Verónica Bolón-Canedo, Juan Touriño, Jorge González-Domínguez, 2019, Inf. Sci..

Case Study of Anomaly Detection and Quality Control of Energy Efficiency and Hygrothermal Comfort in Buildings

Verónica Bolón-Canedo, Javier Tarrío-Saavedra, Salvador Naya, 2019, DATA.

Data analysis and feature selection for predictive maintenance: A case-study in the metallurgic industry

Verónica Bolón-Canedo, Isabel Praça, Goreti Marreiros, 2019, Int. J. Inf. Manag..

An insight on complexity measures and classification in microarray data

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Laura Moran-Fernandez, 2015, 2015 International Joint Conference on Neural Networks (IJCNN).

Ensemble Feature Selection for Rankings of Features

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Iago Porto-Díaz, 2015, IWANN.

A Methodology for Improving Tear Film Lipid Layer Classification

Beatriz Remeseiro, Verónica Bolón-Canedo, Manuel G. Penedo, 2014, IEEE Journal of Biomedical and Health Informatics.

Dealing with inter-expert variability in retinopathy of prematurity: A machine learning approach

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Deniz Erdogmus, 2015, Comput. Methods Programs Biomed..

Testing Different Ensemble Configurations for Feature Selection

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Borja Seijo-Pardo, 2017, Neural Processing Letters.

An Information Theory-Based Feature Selection Framework for Big Data Under Apache Spark

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Francisco Herrera, 2018, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

Data complexity measures for analyzing the effect of SMOTE over microarrays

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Laura Morán-Fernández, 2016, ESANN.

Fast‐mRMR: Fast Minimum Redundancy Maximum Relevance Algorithm for High‐Dimensional Big Data

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Francisco Herrera, 2017, Int. J. Intell. Syst..

Recent advances and emerging challenges of feature selection in the context of big data

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, 2015, Knowl. Based Syst..

An Information Theoretic Feature Selection Framework for Big Data under Apache Spark pdf

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Francisco Herrera, 2016, ArXiv.

Toward the scalability of neural networks through feature selection

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Bertha Guijarro-Berdiñas, 2013, Expert Syst. Appl..

Interferential Tear Film Lipid Layer Classification: An Automatic Dry Eye Test

Beatriz Remeseiro, Verónica Bolón-Canedo, Manuel G. Penedo, 2012, 2012 IEEE 24th International Conference on Tools with Artificial Intelligence.

Multiclass classifiers vs multiple binary classifiers using filters for feature selection

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).

Dealing with heterogeneity in the context of distributed feature selection for classification

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, José Luis Morillo-Salas, 2020, Knowl. Inf. Syst..

Exploring the consequences of distributed feature selection in DNA microarray data

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, 2017, 2017 International Joint Conference on Neural Networks (IJCNN).

A Review of Microarray Datasets: Where to Find Them and Specific Characteristics.

Verónica Bolón-Canedo, Noelia Sánchez-Maroño, Amparo Alonso-Betanzos, 2019, Methods in molecular biology.

Feature Selection Applied to Microarray Data.

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Laura Morán-Fernández, 2019, Methods in molecular biology.

Data classification using an ensemble of filters

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, 2014, Neurocomputing.

On the use of different base classifiers in multiclass problems

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Laura Moran-Fernandez, 2017, Progress in Artificial Intelligence.

Insights into distributed feature ranking

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Gavin Brown, 2019, Inf. Sci..

A distributed wrapper approach for feature selection

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, 2013, ESANN.

Do we need hundreds of classifiers or a good feature selection?

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Laura Morán-Fernández, 2020, ESANN.

On the behavior of feature selection methods dealing with noise and relevance over synthetic scenarios

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, 2011, The 2011 International Joint Conference on Neural Networks.

Preprocessing in High Dimensional Datasets

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Laura Morán-Fernández, 2018 .

Preprocessing in Big Data: New challenges for discretization and feature selection

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, 2017 .

A comparison of performance of K-complex classification methods using feature selection

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, 2016, Inf. Sci..

CUDA-JMI: Acceleration of feature selection on heterogeneous systems

Verónica Bolón-Canedo, Jorge González-Domínguez, Roberto R. Expósito, 2020, Future Gener. Comput. Syst..

Scalability Analysis of mRMR for Microarray Data

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Diego Rego-Fernández, 2014, ICAART.

Local Modeling Classifier for Microarray Gene-Expression Data

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Oscar Fontenla-Romero, 2010, ICANN.

An Agent-Based Prototype for Enhancing Sustainability Behavior at an Academic Environment

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Tony Craig, 2012, PAAMS.

Recent Advances in Ensembles for Feature Selection

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Amparo Alonso-Betanzos, 2018, Intelligent Systems Reference Library.

A review of microarray datasets and applied feature selection methods

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, José Manuel Benítez, 2014, Inf. Sci..

A distributed approach for classification using distance metrics

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Laura Morán-Fernández, 2017, ESANN.

Learning on Vertically Partitioned Data based on Chi-square Feature Selection and Naive Bayes Classification

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Bertha Guijarro-Berdiñas, 2014, ICAART.

A Critical Review of Feature Selection Methods

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, 2015 .

A GMM-based feature extraction technique for the automated diagnosis of Retinopathy of Prematurity

Verónica Bolón-Canedo, Deniz Erdogmus, Michael F. Chiang, 2015, 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI).

Scalability analysis of lter-based methods for feature selection

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Bertha Guijarro-Berdiñas, 2012 .

Analysis of imputation bias for feature selection with missing data

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Julie Josse, 2018, ESANN.

Distributed classification based on distances between probability distributions in feature space

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Pablo Montero-Manso, 2019, Inf. Sci..

A review of feature selection methods on synthetic data

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, 2013, Knowledge and Information Systems.

Biases in feature selection with missing data

Isabelle Guyon, Verónica Bolón-Canedo, Amparo Alonso-Betanzos, 2019, Neurocomputing.

Toward parallel feature selection from vertically partitioned data

Verónica Bolón-Canedo, Noelia Sánchez-Maroño, Joana Cerviño-Rabuñal, 2014, ESANN.

Performance evaluation of unsupervised techniques in cyber-attack anomaly detection

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, João Carneiro, 2019, Journal of Ambient Intelligence and Humanized Computing.

Ensembles for feature selection: A review and future trends

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Amparo Alonso-Betanzos, 2019, Inf. Fusion.

Toward an ensemble of filters for classification

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, 2011, 2011 11th International Conference on Intelligent Systems Design and Applications.

Machine learning for medical applications

Beatriz Remeseiro, Verónica Bolón-Canedo, Amparo Alonso-Betanzos, 2016, ESANN.

Using Data Complexity Measures for Thresholding in Feature Selection Rankers

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Borja Seijo-Pardo, 2016, CAEPIA.

On the use of machine learning techniques for the analysis of spontaneous reactions in automated hearing assessment

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Manuel G. Penedo, 2015, ESANN.

Evaluation of Ensembles for Feature Selection

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, A. Alonso-Betanzos, 2018 .

A Distributed Feature Selection Approach Based on a Complexity Measure

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, 2015, IWANN.

Algorithmic challenges in big data analytics

Beatriz Remeseiro, Verónica Bolón-Canedo, Amparo Alonso-Betanzos, 2017, ESANN.

Introduction to High-Dimensionality

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, 2015 .

Distributed feature selection: An application to microarray data classification

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, 2015, Appl. Soft Comput..

Foundations of Feature Selection

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, 2015 .

Feature selection with limited bit depth mutual information for portable embedded systems

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Gavin Brown, 2020, Knowl. Based Syst..

Predictive Maintenance in the Metallurgical Industry: Data Analysis and Feature Selection

Verónica Bolón-Canedo, Goreti Marreiros, Isabel Praça, 2018, WorldCIST.

A study of performance on microarray data sets for a classifier based on information theoretic learning

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Oscar Fontenla-Romero, 2011, Neural Networks.

Can classification performance be predicted by complexity measures? A study using microarray data

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Laura Moran-Fernandez, 2017, Knowledge and Information Systems.

データ複雑性測度に基づく集中対分散特徴選択法【Powered by NICT】

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Laura Morán-Fernández, 2017 .

On developing an automatic threshold applied to feature selection ensembles

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Borja Seijo-Pardo, 2018, Inf. Fusion.

Feature Selection in Big Image Datasets

Verónica Bolón-Canedo, Beatriz Remeseiro, J. Guzmán Figueira-Domínguez, 2020 .

A framework for cost-based feature selection

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, 2014, Pattern Recognit..

Plus disease: is it more than meets the ICROP?

Verónica Bolón-Canedo, Deniz Erdogmus, Michael F. Chiang, 2016 .

Paving the way for providing teaching feedback in automatic evaluation of open response assignments

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Oscar Luaces, 2017, 2017 International Joint Conference on Neural Networks (IJCNN).

Data discretization: taxonomy and big data challenge

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Francisco Herrera, 2016, WIREs Data Mining Knowl. Discov..

Big-Data Analysis, Cluster Analysis, and Machine-Learning Approaches.

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, A. Alonso-Betanzos, 2018, Advances in experimental medicine and biology.

Other Ensemble Approaches

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, A. Alonso-Betanzos, 2018 .

Challenges and Future Trends for Microarray Analysis.

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Ricardo Cao, 2019, Methods in molecular biology.

Scaling Up Feature Selection: A Distributed Filter Approach

Verónica Bolón-Canedo, Noelia Sánchez-Maroño, Joana Cerviño-Rabuñal, 2013, CAEPIA.

Feature Selection for High-Dimensional Data

Verónica Bolón-Canedo, Noelia Sánchez-Maroño, Amparo Alonso-Betanzos, 2015, Artificial Intelligence: Foundations, Theory, and Algorithms.

Application of Feature Selection to Real Problems

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, 2015 .

Foundations of Ensemble Learning

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, A. Alonso-Betanzos, 2018 .

mC-ReliefF - An Extension of ReliefF for Cost-based Feature Selection

Beatriz Remeseiro, Verónica Bolón-Canedo, Amparo Alonso-Betanzos, 2014, ICAART.

Feature selection and classification in multiple class datasets: An application to KDD Cup 99 dataset

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, 2011, Expert Syst. Appl..

Using a feature selection ensemble on DNA microarray datasets

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Borja Seijo-Pardo, 2016, ESANN.

Feature Selection and Conversion Methods in KDD Cup 99 Dataset: A Comparison of Performance

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, 2010 .

Real-Time Tear Film Classification Through Cost-Based Feature Selection

Beatriz Remeseiro, Verónica Bolón-Canedo, Amparo Alonso-Betanzos, 2015, Trans. Comput. Collect. Intell..

Statistical dependence measure for feature selection in microarray datasets

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, José Carlos Príncipe, 2011, ESANN.

Dimensionality Reduction: Is Feature Selection More Effective Than Random Selection?

Verónica Bolón-Canedo, Laura Morán-Fernández, V. Bolón-Canedo, 2021, International Work-Conference on Artificial and Natural Neural Networks.

A delayed Elastic-Net approach for performing adversarial attacks

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Brais Cancela, 2021, 2020 25th International Conference on Pattern Recognition (ICPR).

Can data placement be effective for Neural Networks classification tasks? Introducing the Orthogonal Loss

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Brais Cancela, 2021, 2020 25th International Conference on Pattern Recognition (ICPR).

How important is data quality? Best classifiers vs best features

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Laura Morán-Fernández, 2021, Neurocomputing.

Exploring Guidelines for Classification of Major Heart Failure Subtypes by Using Machine Learning

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Verónica Bolón-Canedo, 2015, Clinical Medicine Insights. Cardiology.