| An analysis of ensemble pruning techniques based on ordered aggregation G Martinez-Munoz, D Hernández-Lobato, A Suárez IEEE Transactions on Pattern Analysis and Machine Intelligence 31 (2), 245-259, 2008 | 327 | 2008 |
| Pruning in ordered bagging ensembles G Martínez-Muñoz, A Suárez Proceedings of the 23rd international conference on Machine learning, 609-616, 2006 | 184 | 2006 |
| Aggregation ordering in bagging G Martınez-Munoz, A Suárez Proc. of the IASTED International Conference on Artificial Intelligence and …, 2004 | 160 | 2004 |
| Using boosting to prune bagging ensembles G Martinez-Munoz, A Suárez Pattern Recognition Letters 28 (1), 156-165, 2007 | 136 | 2007 |
| Switching class labels to generate classification ensembles G Martínez-Muñoz, A Suárez Pattern Recognition 38 (10), 1483-1494, 2005 | 116 | 2005 |
| Out-of-bag estimation of the optimal sample size in bagging G Martínez-Muñoz, A Suárez Pattern Recognition 43 (1), 143-152, 2010 | 91 | 2010 |
| Dictionary-free categorization of very similar objects via stacked evidence trees G Martinez-Munoz, N Larios, E Mortensen, W Zhang, A Yamamuro, ... 2009 IEEE Conference on Computer Vision and Pattern Recognition, 549-556, 2009 | 80 | 2009 |
| Automated processing and identification of benthic invertebrate samples DA Lytle, G Martínez-Muñoz, W Zhang, N Larios, L Shapiro, R Paasch, ... Journal of the North American Benthological Society 29 (3), 867-874, 2010 | 73 | 2010 |
| How large should ensembles of classifiers be? D Hernández-Lobato, G Martínez-Muñoz, A Suárez Pattern Recognition 46 (5), 1323-1336, 2013 | 70 | 2013 |
| A programming experience of high school students in a virtual world platform M Rico, G Martínez-Muñoz, X Alaman, D Camacho, E Pulido International Journal of Engineering Education 27 (1), 52, 2011 | 63 | 2011 |
| Statistical instance-based pruning in ensembles of independent classifiers D Hernández-Lobato, G Martinez-Munoz, A Suárez IEEE Transactions on Pattern Analysis and Machine Intelligence 31 (2), 364-369, 2008 | 61 | 2008 |
| Empirical analysis and evaluation of approximate techniques for pruning regression bagging ensembles D Hernández-Lobato, G Martínez-Muñoz, A Suárez Neurocomputing 74 (12-13), 2250-2264, 2011 | 48 | 2011 |
| Haar random forest features and SVM spatial matching kernel for stonefly species identification N Larios, B Soran, LG Shapiro, G Martínez-Muñoz, J Lin, TG Dietterich 2010 20th International Conference on Pattern Recognition, 2624-2627, 2010 | 45 | 2010 |
| Pruning in ordered regression bagging ensembles D Hernández-Lobato, G Martínez-Muñoz, A Suárez The 2006 IEEE International Joint Conference on Neural Network Proceedings …, 2006 | 40 | 2006 |
| Vote-boosting ensembles M Sabzevari, G Martínez-Muñoz, A Suárez Pattern Recognition 83, 119-133, 2018 | 33 | 2018 |
| Class-switching neural network ensembles G Martínez-Muñoz, A Sánchez-Martínez, D Hernández-Lobato, A Suárez Neurocomputing 71 (13-15), 2521-2528, 2008 | 32 | 2008 |
| Using a SPOC to flip the classroom G Martínez-Muñoz, E Pulido 2015 IEEE global Engineering education conference (EDUCON), 431-436, 2015 | 31 | 2015 |
| Engineering of silicon surfaces at the micro-and nanoscales for cell adhesion and migration control V Torres-Costa, G Martínez-Muñoz, V Sánchez-Vaquero, Á Muñoz-Noval, ... International journal of nanomedicine 7, 623, 2012 | 24 | 2012 |
| Using all data to generate decision tree ensembles G Martínez-Muñoz, A Suárez IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and …, 2004 | 23 | 2004 |
| A double pruning scheme for boosting ensembles V Soto, S García-Moratilla, G Martínez-Muñoz, D Hernández-Lobato, ... IEEE transactions on cybernetics 44 (12), 2682-2695, 2014 | 21 | 2014 |
Alberto SuárezProfessor of Artificial Intelligence, Computer Science Department, Universidad Autónoma de MadridVerifierad e-postadress på uam.es
