Feature selection for multi-label naive Bayes classification ML Zhang, JM Peña, V Robles Information Sciences 179 (19), 3218-3229, 2009 | 630 | 2009 |
Mechanistic models versus machine learning, a fight worth fighting for the biological community? RE Baker, JM Pena, J Jayamohan, A Jérusalem Biology letters 14 (5), 20170660, 2018 | 337 | 2018 |
Large scale global optimization: Experimental results with MOS-based hybrid algorithms A LaTorre, S Muelas, JM Peña 2013 IEEE congress on evolutionary computation, 2742-2749, 2013 | 142 | 2013 |
A MOS-based dynamic memetic differential evolution algorithm for continuous optimization: a scalability test A LaTorre, S Muelas, JM Peña Soft Computing-A Fusion of Foundations, Methodologies and Applications 15 …, 2011 | 136 | 2011 |
A comprehensive comparison of large scale global optimizers A LaTorre, S Muelas, JM Peña Information Sciences 316, 517-549, 2015 | 130 | 2015 |
GA-EDA: Hybrid evolutionary algorithm using genetic and estimation of distribution algorithms J Pena, V Robles, P Larranaga, V Herves, F Rosales, M Perez Innovations in Applied Artificial Intelligence, 361-371, 2004 | 97 | 2004 |
A multicenter study of the early detection of synaptic dysfunction in Mild Cognitive Impairment using Magnetoencephalography-derived functional connectivity F Maestú, JM Peña, P Garcés, S González, R Bajo, A Bagic, P Cuesta, ... NeuroImage: Clinical 9, 103-109, 2015 | 89 | 2015 |
An improved Bayesian structural EM algorithm for learning Bayesian networks for clustering JM Peña, JA Lozano, P Larrañaga Pattern Recognition Letters 21 (8), 779-786, 2000 | 78 | 2000 |
Multiple Offspring Sampling in Large Scale Global Optimization A LaTorre, S Muelas, JM Pena Evolutionary Computation (CEC), 2012 IEEE Congress on, 1-8, 2012 | 75 | 2012 |
Bayesian network multi-classifiers for protein secondary structure prediction V Robles, P Larranaga, JM Pena, E Menasalvas, MS Perez, V Herves, ... Artificial Intelligence in Medicine 31 (2), 117-136, 2004 | 71 | 2004 |
Segmentation of neuronal nuclei based on clump splitting and a two-step binarization of images A LaTorre, L Alonso-Nanclares, S Muelas, JM Peña, J DeFelipe Expert Systems with Applications 40 (16), 6521-6530, 2013 | 64 | 2013 |
A computational model coupling mechanics and electrophysiology in spinal cord injury A Jérusalem, JA García-Grajales, A Merchán-Pérez, JM Peña Biomechanics and modeling in mechanobiology 13, 883-896, 2014 | 61 | 2014 |
A variable neighborhood search algorithm for the optimization of a dial-a-ride problem in a large city S Muelas, A LaTorre, JM Peña Expert Systems with Applications 40 (14), 5516-5531, 2013 | 61 | 2013 |
A distributed VNS algorithm for optimizing dial-a-ride problems in large-scale scenarios S Muelas, A LaTorre, JM Pena Transportation Research Part C: Emerging Technologies 54, 110-130, 2015 | 58 | 2015 |
Design and implementation of a data mining grid-aware architecture MS Pérez, A Sánchez, V Robles, P Herrero, JM Peña Future Generation Computer Systems 23 (1), 42-47, 2007 | 58 | 2007 |
A memetic differential evolution algorithm for continuous optimization S Muelas, A La Torre, J Pea Intelligent Systems Design and Applications, 2009. ISDA'09. Ninth …, 2009 | 46 | 2009 |
Application of rough sets algorithms to prediction of aircraft component failure J Peña, S Létourneau, F Famili Advances in Intelligent Data Analysis, 473-484, 1999 | 42 | 1999 |
Generation and recovery of airborne delays in air transport S Belkoura, JM Peña, M Zanin Transportation Research Part C: Emerging Technologies 69, 436-450, 2016 | 41 | 2016 |
Scaling laws in bacterial genomes: A side-effect of selection of mutational robustness? G Beslon, DP Parsons, Y Sanchez-Dehesa, JM Peña, C Knibbe BioSystems 102 (1), 32-40, 2010 | 41 | 2010 |
Adapting the weka data mining toolkit to a grid based environment M Perez, A Sánchez, P Herrero, V Robles, J Peña Advances in Web Intelligence, 819-820, 2005 | 38 | 2005 |