Gonzalo Martínez-Muñoz

Publication Activity (10 Years)

Years Active: 2004-2024
Publications (10 Years): 23

Top Topics

Gradient Boosting

Ensemble Methods

Feature Importance

Top Venues

Int. J. Mach. Learn. Cybern.

Publications

Rima Guilal, Nesma Settouti, Gonzalo Martínez-Muñoz, Mohammed Amine Chikh
Feature importance analysis for a highly unbalanced multiple myeloma data classification. Int. J. Medical Eng. Informatics 16 (3) (2024)
Gonzalo Martínez-Muñoz, Miguel Ángel Álvarez-Rodríguez, Estrella Pulido-Cañabate
Video Visualization Profile Analysis in Online Courses. IEEE Trans. Educ. 67 (4) (2024)
Seyedsaman Emami, Gonzalo Martínez-Muñoz
Deep Learning for Multi-Output Regression Using Gradient Boosting. IEEE Access 12 (2024)
Seyedsaman Emami, Gonzalo Martínez-Muñoz
Boosting the performance of deep learning: A gradient Boosting approach to training convolutional and deep neural network. CoRR (2023)
Seyedsaman Emami, Carlos Ruiz Pastor, Gonzalo Martínez-Muñoz
Multi-Task Gradient Boosting. HAIS (2023)
Seyedsaman Emami, Gonzalo Martínez-Muñoz
Condensed Gradient Boosting. CoRR (2022)
David Nevado, Gonzalo Martínez-Muñoz, Alberto Suárez
SVM Ensembles on a Budget. ICANN (4) (2022)
Maryam Sabzevari, Gonzalo Martínez-Muñoz, Alberto Suárez
Building heterogeneous ensembles by pooling homogeneous ensembles. Int. J. Mach. Learn. Cybern. 13 (2) (2022)
Amgad M. Mohammed, Enrique Onieva, Michal Wozniak, Gonzalo Martínez-Muñoz
An analysis of heuristic metrics for classifier ensemble pruning based on ordered aggregation. Pattern Recognit. 124 (2022)
Seyedsaman Emami, Gonzalo Martínez-Muñoz
Multioutput Regression Neural Network Training via Gradient Boosting. ESANN (2022)
Maryam Sabzevari, Gonzalo Martínez-Muñoz, Alberto Suárez
Correction to: Building heterogeneous ensembles by pooling homogeneous ensembles. Int. J. Mach. Learn. Cybern. 13 (2) (2022)
Candice Bentéjac, Anna Csörgo, Gonzalo Martínez-Muñoz
A comparative analysis of gradient boosting algorithms. Artif. Intell. Rev. 54 (3) (2021)
Vicenzo Abichequer Sangalli, Gonzalo Martínez-Muñoz, Estrella Pulido-Cañabate
Identifying Cheating Users in Online Courses. EDUCON (2020)
Candice Bentéjac, Anna Csörgo, Gonzalo Martínez-Muñoz
A Comparative Analysis of XGBoost. CoRR (2019)
Gonzalo Martínez-Muñoz
Sequential Training of Neural Networks with Gradient Boosting. CoRR (2019)
Maryam Sabzevari, Gonzalo Martínez-Muñoz, Alberto Suárez
A two-stage ensemble method for the detection of class-label noise. Neurocomputing 275 (2018)
Pablo de Viña, Gonzalo Martínez-Muñoz
Using Bag-of-Little Bootstraps for Efficient Ensemble Learning. ICANN (1) (2018)
Maryam Sabzevari, Gonzalo Martínez-Muñoz, Alberto Suárez
Pooling homogeneous ensembles to build heterogeneous ensembles. CoRR (2018)
Maryam Sabzevari, Gonzalo Martínez-Muñoz, Alberto Suárez
Vote-boosting ensembles. Pattern Recognit. 83 (2018)
Maryam Sabzevari, Gonzalo Martínez-Muñoz, Alberto Suárez
Randomization vs Optimization in SVM Ensembles. ICANN (2) (2018)
Ángel Pérez-Lemonche, Gonzalo Martínez-Muñoz, Estrella Pulido-Cañabate
Analysing Event Transitions to Discover Student Roles and Predict Grades in MOOCs. ICANN (2) (2017)
Víctor Soto, Alberto Suárez, Gonzalo Martínez-Muñoz
An urn model for majority voting in classification ensembles. NIPS (2016)
Maryam Sabzevari, Gonzalo Martínez-Muñoz, Alberto Suárez
Vote-boosting ensembles. CoRR (2016)
Maryam Sabzevari, Gonzalo Martínez-Muñoz, Alberto Suárez
Small margin ensembles can be robust to class-label noise. Neurocomputing 160 (2015)
Gonzalo Martínez-Muñoz, Estrella Pulido
Using a SPOC to flip the classroom. EDUCON (2015)
Daniel Hernández-Lobato, Ioannis Katakis, Gonzalo Martínez-Muñoz, Ioannis Partalas
Special Issue on "Solving complex machine learning problems with ensemble methods". Neurocomputing 150 (2015)
Víctor Soto, Sergio García-Moratilla, Gonzalo Martínez-Muñoz, Daniel Hernández-Lobato, Alberto Suárez
A Double Pruning Scheme for Boosting Ensembles. IEEE Trans. Cybern. 44 (12) (2014)
Maryam Sabzevari, Gonzalo Martínez-Muñoz, Alberto Suárez
Improving the Robustness of Bagging with Reduced Sampling Size. ESANN (2014)
Luis Fernando Lago-Fernández, Jesús Aragón, Gonzalo Martínez-Muñoz, Ana M. González, Manuel A. Sánchez-Montañés
Cluster validation in problems with increasing dimensionality and unbalanced clusters. Neurocomputing 123 (2014)
Daniel Hernández-Lobato, Gonzalo Martínez-Muñoz, Alberto Suárez
How large should ensembles of classifiers be? Pattern Recognit. 46 (5) (2013)
Luis Fernando Lago-Fernández, Gonzalo Martínez-Muñoz, Ana M. González, Manuel A. Sánchez-Montañés
Evaluation of Negentropy-based Cluster Validation Techniques in Problems with Increasing Dimensionality. ICPRAM (1) (2012)
Daniel Hernández-Lobato, Gonzalo Martínez-Muñoz, Alberto Suárez
On the Independence of the Individual Predictions in Parallel Randomized Ensembles. ESANN (2012)
Daniel Hernández-Lobato, Gonzalo Martínez-Muñoz, Alberto Suárez
Inference on the prediction of ensembles of infinite size. Pattern Recognit. 44 (7) (2011)
Daniel Hernández-Lobato, Gonzalo Martínez-Muñoz, Alberto Suárez
Empirical analysis and evaluation of approximate techniques for pruning regression bagging ensembles. Neurocomputing 74 (12-13) (2011)
Richard N. Rojas-Bello, Luis Fernando Lago-Fernández, Gonzalo Martínez-Muñoz, Manuel A. Sánchez-Montañés
A comparison of techniques for robust gender recognition. ICIP (2011)
Víctor Soto, Gonzalo Martínez-Muñoz, Daniel Hernández-Lobato, Alberto Suárez
A Double Pruning Algorithm for Classification Ensembles. MCS (2010)
Gonzalo Martínez-Muñoz, Alberto Suárez
Out-of-bag estimation of the optimal sample size in bagging. Pattern Recognit. 43 (1) (2010)
Natalia Larios, Bilge Soran, Linda G. Shapiro, Gonzalo Martínez-Muñoz, Junyuan Lin, Thomas G. Dietterich
Haar Random Forest Features and SVM Spatial Matching Kernel for Stonefly Species Identification. ICPR (2010)
Gonzalo Martínez-Muñoz, Daniel Hernández-Lobato, Alberto Suárez
An Analysis of Ensemble Pruning Techniques Based on Ordered Aggregation. IEEE Trans. Pattern Anal. Mach. Intell. 31 (2) (2009)
Gonzalo Martínez-Muñoz, Daniel Hernández-Lobato, Alberto Suárez
Statistical Instance-Based Ensemble Pruning for Multi-class Problems. ICANN (1) (2009)
Daniel Hernández-Lobato, Gonzalo Martínez-Muñoz, Alberto Suárez
Statistical Instance-Based Pruning in Ensembles of Independent Classifiers. IEEE Trans. Pattern Anal. Mach. Intell. 31 (2) (2009)
Gonzalo Martínez-Muñoz, Natalia Larios Delgado, Eric N. Mortensen, Wei Zhang, Asako Yamamuro, Robert Paasch, Nadia Payet, David A. Lytle, Linda G. Shapiro, Sinisa Todorovic, Andrew Moldenke, Thomas G. Dietterich
Dictionary-free categorization of very similar objects via stacked evidence trees. CVPR (2009)
Gonzalo Martínez-Muñoz, Aitor Sánchez-Martínez, Daniel Hernández-Lobato, Alberto Suárez
Class-switching neural network ensembles. Neurocomputing 71 (13-15) (2008)
Gonzalo Martínez-Muñoz, Alberto Suárez
Using boosting to prune bagging ensembles. Pattern Recognit. Lett. 28 (1) (2007)
Gonzalo Martínez-Muñoz, Daniel Hernández-Lobato, Alberto Suárez
Selection of Decision Stumps in Bagging Ensembles. ICANN (1) (2007)
Daniel Hernández-Lobato, Gonzalo Martínez-Muñoz, Alberto Suárez
Out of Bootstrap Estimation of Generalization Error Curves in Bagging Ensembles. IDEAL (2007)
Gonzalo Martínez-Muñoz, Aitor Sánchez-Martínez, Daniel Hernández-Lobato, Alberto Suárez
Building Ensembles of Neural Networks with Class-Switching. ICANN (1) (2006)
Daniel Hernández-Lobato, Gonzalo Martínez-Muñoz, Alberto Suárez
Pruning in Ordered Regression Bagging Ensembles. IJCNN (2006)
Sergio García-Moratilla, Gonzalo Martínez-Muñoz, Alberto Suárez
Evaluation of Decision Tree Pruning with Subadditive Penalties. IDEAL (2006)
Gonzalo Martínez-Muñoz, Alberto Suárez
Pruning in ordered bagging ensembles. ICML (2006)
Gonzalo Martínez-Muñoz, Alberto Suárez
Switching class labels to generate classification ensembles. Pattern Recognit. 38 (10) (2005)
Gonzalo Martínez-Muñoz, Alberto Suárez
Using all data to generate decision tree ensembles. IEEE Trans. Syst. Man Cybern. Part C 34 (4) (2004)