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ORCIDGonzalo Martínez-Muñoz
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2020 – today
- 2024
[j24]Seyedsaman Emami
, Gonzalo Martínez-Muñoz:
Deep Learning for Multi-Output Regression Using Gradient Boosting. IEEE Access 12: 17760-17772 (2024)- [j23]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): 199-209 (2024) - [j22]Gonzalo Martínez-Muñoz, Miguel Ángel Álvarez-Rodríguez, Estrella Pulido-Cañabate:
Video Visualization Profile Analysis in Online Courses. IEEE Trans. Educ. 67(4): 629-638 (2024) - 2023
- [j21]Seyedsaman Emami, Gonzalo Martínez-Muñoz:
Sequential Training of Neural Networks With Gradient Boosting. IEEE Access 11: 42738-42750 (2023) - [c23]Seyedsaman Emami, Carlos Ruiz Pastor, Gonzalo Martínez-Muñoz:
Multi-Task Gradient Boosting. HAIS 2023: 97-107 - [i6]Seyedsaman Emami, Gonzalo Martínez-Muñoz:
A Gradient Boosting Approach for Training Convolutional and Deep Neural Networks. CoRR abs/2302.11327 (2023) - 2022
- [j20]Maryam Sabzevari, Gonzalo Martínez-Muñoz, Alberto Suárez:
Building heterogeneous ensembles by pooling homogeneous ensembles. Int. J. Mach. Learn. Cybern. 13(2): 551-558 (2022) - [j19]Maryam Sabzevari, Gonzalo Martínez-Muñoz, Alberto Suárez:
Correction to: Building heterogeneous ensembles by pooling homogeneous ensembles. Int. J. Mach. Learn. Cybern. 13(2): 559 (2022) - [j18]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: 108493 (2022) - [c22]Seyedsaman Emami, Gonzalo Martínez-Muñoz:
Multioutput Regression Neural Network Training via Gradient Boosting. ESANN 2022 - [c21]David Nevado, Gonzalo Martínez-Muñoz, Alberto Suárez:
SVM Ensembles on a Budget. ICANN (4) 2022: 297-308 - [i5]Seyedsaman Emami, Gonzalo Martínez-Muñoz:
Condensed Gradient Boosting. CoRR abs/2211.14599 (2022) - 2021
- [j17]Candice Bentéjac, Anna Csörgo, Gonzalo Martínez-Muñoz:
A comparative analysis of gradient boosting algorithms. Artif. Intell. Rev. 54(3): 1937-1967 (2021) - 2020
- [c20]Vicenzo Abichequer Sangalli, Gonzalo Martínez-Muñoz, Estrella Pulido-Cañabate:
Identifying Cheating Users in Online Courses. EDUCON 2020: 1168-1175
2010 – 2019
- 2019
- [i4]Gonzalo Martínez-Muñoz:
Sequential Training of Neural Networks with Gradient Boosting. CoRR abs/1909.12098 (2019) - [i3]Candice Bentéjac, Anna Csörgo, Gonzalo Martínez-Muñoz:
A Comparative Analysis of XGBoost. CoRR abs/1911.01914 (2019) - 2018
- [j16]Maryam Sabzevari, Gonzalo Martínez-Muñoz, Alberto Suárez:
A two-stage ensemble method for the detection of class-label noise. Neurocomputing 275: 2374-2383 (2018) - [j15]Maryam Sabzevari, Gonzalo Martínez-Muñoz, Alberto Suárez:
Vote-boosting ensembles. Pattern Recognit. 83: 119-133 (2018) - [c19]Maryam Sabzevari, Gonzalo Martínez-Muñoz, Alberto Suárez:
Randomization vs Optimization in SVM Ensembles. ICANN (2) 2018: 415-421 - [c18]Pablo de Viña, Gonzalo Martínez-Muñoz:
Using Bag-of-Little Bootstraps for Efficient Ensemble Learning. ICANN (1) 2018: 538-545 - [i2]Maryam Sabzevari, Gonzalo Martínez-Muñoz, Alberto Suárez:
Pooling homogeneous ensembles to build heterogeneous ensembles. CoRR abs/1802.07877 (2018) - 2017
- [c17]Ángel Pérez-Lemonche, Gonzalo Martínez-Muñoz, Estrella Pulido-Cañabate:
Analysing Event Transitions to Discover Student Roles and Predict Grades in MOOCs. ICANN (2) 2017: 224-232 - 2016
- [c16]Víctor Soto, Alberto Suárez, Gonzalo Martínez-Muñoz:
An urn model for majority voting in classification ensembles. NIPS 2016: 4430-4438 - [i1]Maryam Sabzevari, Gonzalo Martínez-Muñoz, Alberto Suárez:
Vote-boosting ensembles. CoRR abs/1606.09458 (2016) - 2015
- [j14]Daniel Hernández-Lobato, Ioannis Katakis, Gonzalo Martínez-Muñoz, Ioannis Partalas:
Special Issue on "Solving complex machine learning problems with ensemble methods". Neurocomputing 150: 402-403 (2015) - [j13]Maryam Sabzevari, Gonzalo Martínez-Muñoz, Alberto Suárez:
Small margin ensembles can be robust to class-label noise. Neurocomputing 160: 18-33 (2015) - [c15]Gonzalo Martínez-Muñoz, Estrella Pulido:
Using a SPOC to flip the classroom. EDUCON 2015: 431-436 - 2014
- [j12]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: 33-39 (2014) - [j11]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): 2682-2695 (2014) - [c14]Maryam Sabzevari, Gonzalo Martínez-Muñoz, Alberto Suárez:
Improving the Robustness of Bagging with Reduced Sampling Size. ESANN 2014 - 2013
- [j10]Daniel Hernández-Lobato, Gonzalo Martínez-Muñoz, Alberto Suárez:
How large should ensembles of classifiers be? Pattern Recognit. 46(5): 1323-1336 (2013) - 2012
- [c13]Daniel Hernández-Lobato, Gonzalo Martínez-Muñoz, Alberto Suárez:
On the Independence of the Individual Predictions in Parallel Randomized Ensembles. ESANN 2012 - [c12]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: 235-241 - 2011
- [j9]Daniel Hernández-Lobato, Gonzalo Martínez-Muñoz, Alberto Suárez:
Empirical analysis and evaluation of approximate techniques for pruning regression bagging ensembles. Neurocomputing 74(12-13): 2250-2264 (2011) - [j8]Daniel Hernández-Lobato, Gonzalo Martínez-Muñoz, Alberto Suárez:
Inference on the prediction of ensembles of infinite size. Pattern Recognit. 44(7): 1426-1434 (2011) - [c11]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: 561-564 - 2010
- [j7]Gonzalo Martínez-Muñoz, Alberto Suárez:
Out-of-bag estimation of the optimal sample size in bagging. Pattern Recognit. 43(1): 143-152 (2010) - [c10]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: 2624-2627 - [c9]Víctor Soto, Gonzalo Martínez-Muñoz, Daniel Hernández-Lobato, Alberto Suárez:
A Double Pruning Algorithm for Classification Ensembles. MCS 2010: 104-113
2000 – 2009
- 2009
- [j6]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): 245-259 (2009) - [j5]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): 364-369 (2009) - [c8]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: 549-556 - [c7]Gonzalo Martínez-Muñoz, Daniel Hernández-Lobato, Alberto Suárez:
Statistical Instance-Based Ensemble Pruning for Multi-class Problems. ICANN (1) 2009: 90-99 - 2008
- [j4]Gonzalo Martínez-Muñoz, Aitor Sánchez-Martínez, Daniel Hernández-Lobato, Alberto Suárez:
Class-switching neural network ensembles. Neurocomputing 71(13-15): 2521-2528 (2008) - 2007
- [j3]Gonzalo Martínez-Muñoz, Alberto Suárez:
Using boosting to prune bagging ensembles. Pattern Recognit. Lett. 28(1): 156-165 (2007) - [c6]Gonzalo Martínez-Muñoz, Daniel Hernández-Lobato, Alberto Suárez:
Selection of Decision Stumps in Bagging Ensembles. ICANN (1) 2007: 319-328 - [c5]Daniel Hernández-Lobato, Gonzalo Martínez-Muñoz, Alberto Suárez:
Out of Bootstrap Estimation of Generalization Error Curves in Bagging Ensembles. IDEAL 2007: 47-56 - 2006
- [c4]Gonzalo Martínez-Muñoz, Aitor Sánchez-Martínez, Daniel Hernández-Lobato, Alberto Suárez:
Building Ensembles of Neural Networks with Class-Switching. ICANN (1) 2006: 178-187 - [c3]Gonzalo Martínez-Muñoz, Alberto Suárez:
Pruning in ordered bagging ensembles. ICML 2006: 609-616 - [c2]Sergio García-Moratilla, Gonzalo Martínez-Muñoz, Alberto Suárez:
Evaluation of Decision Tree Pruning with Subadditive Penalties. IDEAL 2006: 995-1002 - [c1]Daniel Hernández-Lobato, Gonzalo Martínez-Muñoz, Alberto Suárez:
Pruning in Ordered Regression Bagging Ensembles. IJCNN 2006: 1266-1273 - 2005
- [j2]Gonzalo Martínez-Muñoz, Alberto Suárez:
Switching class labels to generate classification ensembles. Pattern Recognit. 38(10): 1483-1494 (2005) - 2004
- [j1]Gonzalo Martínez-Muñoz, Alberto Suárez:
Using all data to generate decision tree ensembles. IEEE Trans. Syst. Man Cybern. Part C 34(4): 393-397 (2004)
Coauthor Index
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