A novel frank–wolfe algorithm. analysis and applications to large-scale svm training R Ñanculef, E Frandi, C Sartori, H Allende Information Sciences 285, 66-99, 2014 | 47 | 2014 |
Automating configuration of convolutional neural network hyperparameters using genetic algorithm F Johnson, A Valderrama, C Valle, B Crawford, R Soto, R Ñanculef IEEE Access 8, 156139-156152, 2020 | 40 | 2020 |
Efficient classification of multi-labeled text streams by clashing R Nanculef, I Flaounas, N Cristianini Expert Systems with Applications 41 (11), 5431-5450, 2014 | 40 | 2014 |
Robust alternating adaboost H Allende-Cid, R Salas, H Allende, R Nanculef Iberoamerican Congress on Pattern Recognition, 427-436, 2007 | 23 | 2007 |
Robust bootstrapping neural networks H Allende, R Ñanculef, R Salas MICAI 2004: Advances in Artificial Intelligence: Third Mexican International …, 2004 | 19 | 2004 |
Fast and scalable Lasso via stochastic Frank–Wolfe methods with a convergence guarantee E Frandi, R Ñanculef, S Lodi, C Sartori, JAK Suykens Machine Learning 104, 195-221, 2016 | 15 | 2016 |
Ad-svms: A light extension of svms for multicategory classification R Nanculef, C Concha, H Allende, D Candel, C Moraga International Journal of Hybrid Intelligent Systems 6 (2), 69-79, 2009 | 15 | 2009 |
Calcified plaque detection in IVUS sequences: Preliminary results using convolutional nets S Balocco, M González, R Ñanculef, P Radeva, G Thomas Progress in Artificial Intelligence and Pattern Recognition: 6th …, 2018 | 14 | 2018 |
Single-pass distributed learning of multi-class svms using core-sets S Lodi, R Nanculef, C Sartori Proceedings of the 2010 SIAM international conference on data mining, 257-268, 2010 | 13 | 2010 |
Training Convolutional Nets to Detect Calcified Plaque in IVUS Sequences R Ñanculef, P Radeva, S Balocco Intravascular Ultrasound, 141-158, 2020 | 11 | 2020 |
A binary variational autoencoder for hashing F Mena, R Nanculef Progress in Pattern Recognition, Image Analysis, Computer Vision, and …, 2019 | 11 | 2019 |
A partan-accelerated frank-wolfe algorithm for large-scale svm classification E Frandi, R Ñanculef, JAK Suykens 2015 International Joint Conference on Neural Networks (IJCNN), 1-8, 2015 | 10 | 2015 |
A new algorithm for training SVMs using approximate minimal enclosing balls E Frandi, MG Gasparo, S Lodi, R Ñanculef, C Sartori Progress in Pattern Recognition, Image Analysis, Computer Vision, and …, 2010 | 10 | 2010 |
Complexity issues and randomization strategies in Frank-Wolfe algorithms for machine learning E Frandi, R Ñanculef, J Suykens arXiv preprint arXiv:1410.4062, 2014 | 9 | 2014 |
Training support vector machines using Frank–Wolfe optimization methods E Frandi, R Nanculef, MG Gasparo, S Lodi, C Sartori International Journal of Pattern Recognition and Artificial Intelligence 27 …, 2013 | 9 | 2013 |
Training regression ensembles by sequential target correction and resampling R Ñanculef, C Valle, H Allende, C Moraga Information Sciences 195, 154-174, 2012 | 8 | 2012 |
Ensembles methods for machine learning pattern recognition and machine vision H Allende, C Moraga, R Ñanculef, R Salas Series Information Sciences & Tecnology. In honor and memory of Prof. KS. Fu …, 2010 | 8 | 2010 |
Ensemble learning with local diversity R Nanculef, C Valle, H Allende, C Moraga International Conference on Artificial Neural Networks, 264-273, 2006 | 8 | 2006 |
Training support vector machines using Frank-Wolfe methods E Frandi, MG Gasparo, S Lodi, R Ñanculef, C Sartori International Journal of Pattern Recognition and Artificial Intelligence 27 (3), 2011 | 7 | 2011 |
A sequential minimal optimization algorithm for the all-distances support vector machine D Candel, R Ñanculef, C Concha, H Allende Progress in Pattern Recognition, Image Analysis, Computer Vision, and …, 2010 | 7 | 2010 |