Pablo M. Granitto

Comput. Electron. Agric., 2018

From FATS to feets: Further improvements to an astronomical feature extraction tool based on machine learning.

[BibT_eX]

[DOI]

Astron. Comput., 2018

2017

Improved multiclass feature selection via list combination.

[BibT_eX]

[DOI]

Javier Izetta

Expert Syst. Appl., 2017

Class-Splitting Generative Adversarial Networks.

[BibT_eX]

[DOI]

CoRR, 2017

Corral framework: Trustworthy and fully functional data intensive parallel astronomical pipelines.

[BibT_eX]

[DOI]

Astron. Comput., 2017

2016

Finding local leaf vein patterns for legume characterization and classification.

[BibT_eX]

[DOI]

Mach. Vis. Appl., 2016

Clustering using PK-D: A connectivity and density dissimilarity.

[BibT_eX]

[DOI]

Expert Syst. Appl., 2016

Inferring unknown biological function by integration of GO annotations and gene expression data.

[BibT_eX]

[DOI]

CoRR, 2016

Deep learning for plant identification using vein morphological patterns.

[BibT_eX]

[DOI]

Comput. Electron. Agric., 2016

2015

Nonstationary regression with support vector machines.

[BibT_eX]

[DOI]

Neural Comput. Appl., 2015

2014

Automatic classification of legumes using leaf vein image features.

[BibT_eX]

[DOI]

Pattern Recognit., 2014

Multiscale recognition of legume varieties based on leaf venation images.

[BibT_eX]

[DOI]

Expert Syst. Appl., 2014

Hybrid Consensus Learning for Legume Species and Cultivars Classification.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2014 Workshops, 2014

2013

How Many Clusters: A Validation Index for Arbitrary-Shaped Clusters.

[BibT_eX]

[DOI]

IEEE ACM Trans. Comput. Biol. Bioinform., 2013

Spot defects detection in cDNA microarray images.

[BibT_eX]

[DOI]

Juan C. Gómez

Pattern Anal. Appl., 2013

Abrupt change detection with One-Class Time-Adaptive Support Vector Machines.

[BibT_eX]

[DOI]

Expert Syst. Appl., 2013

2012

Legume Identification by Leaf Vein Images Classification.

[BibT_eX]

[DOI]

Proceedings of the Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 2012

A Simple Hybrid Method for Semi-Supervised Learning.

[BibT_eX]

[DOI]

Proceedings of the Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 2012

2011

Solving Nonstationary Classification Problems With Coupled Support Vector Machines.

[BibT_eX]

[DOI]

IEEE Trans. Neural Networks, 2011

Evaluation of a new hybrid algorithm for highly imbalanced classification problems.

[BibT_eX]

[DOI]

Int. J. Hybrid Intell. Syst., 2011

Clustering gene expression data with a penalized graph-based metric.

[BibT_eX]

[DOI]

BMC Bioinform., 2011

Improved Gene Expression Clustering with the Parameter-Free PKNNG Metric.

[BibT_eX]

[DOI]

Proceedings of the Advances in Bioinformatics and Computational Biology, 2011

Unsupervized Data-Driven Partitioning of Multiclass Problems.

[BibT_eX]

[DOI]

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2011, 2011

2010

Penalized K-Nearest-Neighbor-Graph Based Metrics for Clustering

[BibT_eX]

[DOI]

CoRR, 2010

Learning to Discover Faulty Spots in cDNA Microarrays.

[BibT_eX]

[DOI]

Juan C. Gómez

Proceedings of the Advances in Artificial Intelligence, 2010

SVM Based Feature Selection: Why Are We Using the Dual?

[BibT_eX]

[DOI]

Javier Izetta

Proceedings of the Advances in Artificial Intelligence, 2010

Improved Graph-Based Metrics for Clustering High-Dimensional Datasets.

[BibT_eX]

[DOI]

Proceedings of the Advances in Artificial Intelligence, 2010

2009

Feature selection on wide multiclass problems using OVA-RFE.

[BibT_eX]

[DOI]

Andrés Burgos

Inteligencia Artif., 2009

2008

Time-Adaptive Support Vector Machines.

[BibT_eX]

[DOI]

Inteligencia Artif., 2008

ISOMAP based metrics for clustering.

[BibT_eX]

[DOI]

Inteligencia Artif., 2008

Efficient Feature Selection for PTR-MS Fingerprinting of Agroindustrial Products.

[BibT_eX]

[DOI]

Proceedings of the Artificial Neural Networks, 2008

REPMAC: A New Hybrid Approach to Highly Imbalanced Classification Problems.

[BibT_eX]

[DOI]

Proceedings of the 8th International Conference on Hybrid Intelligent Systems (HIS 2008), 2008

2007

Symmetric-embedding prediction of the CATS benchmark.

[BibT_eX]

[DOI]

Neurocomputing, 2007

Gene Set Enrichment Analysis Using Non-parametric Scores.

[BibT_eX]

[DOI]

Proceedings of the Advances in Bioinformatics and Computational Biology, 2007

2005

Neural network ensembles: evaluation of aggregation algorithms.

[BibT_eX]

[DOI]

Artif. Intell., 2005

2003

Artificial Neural Network Learning of Nonstationary Behavior in Time Series.

[BibT_eX]

[DOI]

María I. Széliga

Int. J. Neural Syst., 2003

2002

Extracting Driving Signals from Non-Stationary Time Series.

[BibT_eX]

[DOI]

María I. Széliga

Proceedings of the 7th Brazilian Symposium on Neural Networks (SBRN 2002), 2002

Aggregation Algorithms for Neural Network Ensemble Construction .

[BibT_eX]

[DOI]

Proceedings of the 7th Brazilian Symposium on Neural Networks (SBRN 2002), 2002

2001

A Late-Stopping Method for Optimal Aggregation of Neural Networks.

[BibT_eX]

[DOI]

Int. J. Neural Syst., 2001

A Learning Algorithm For Neural Network Ensembles.

[BibT_eX]

[DOI]

Inteligencia Artif., 2001

2000

Selecting Diverse Members of Neural Network Ensembles.

[BibT_eX]

[DOI]