| SimpleMKL A Rakotomamonjy, F Bach, S Canu, Y Grandvalet Journal of Machine Learning Research 9, 2491-2521, 2008 | 1645 | 2008 |
| Variable selection using SVM-based criteria A Rakotomamonjy Journal of machine learning research 3 (Mar), 1357-1370, 2003 | 843 | 2003 |
| A review of classification algorithms for EEG-based brain–computer interfaces: a 10 year update F Lotte, L Bougrain, A Cichocki, M Clerc, M Congedo, A Rakotomamonjy, ... Journal of neural engineering 15 (3), 031005, 2018 | 708 | 2018 |
| Svm and kernel methods matlab toolbox S Canu, Y Grandvalet, V Guigue, A Rakotomamonjy Perception Systmes et Information, INSA de Rouen, Rouen, France 2, 2005 | 567 | 2005 |
| Optimal transport for domain adaptation N Courty, R Flamary, D Tuia, A Rakotomamonjy IEEE transactions on pattern analysis and machine intelligence 39 (9), 1853-1865, 2016 | 560* | 2016 |
| BCI competition III: Dataset II-ensemble of SVMs for BCI P300 speller A Rakotomamonjy, V Guigue Biomedical Engineering, IEEE Transactions on 55 (3), 1147-1154, 2008 | 540 | 2008 |
| Pedestrian detection using infrared images and histograms of oriented gradients F Suard, A Rakotomamonjy, A Bensrhair, A Broggi Intelligent Vehicles Symposium, 2006 IEEE, 206-212, 2006 | 378 | 2006 |
| More efficiency in multiple kernel learning A Rakotomamonjy, F Bach, S Canu, Y Grandvalet Proceedings of the 24th international conference on Machine learning, 775-782, 2007 | 368 | 2007 |
| Recovering sparse signals with a certain family of nonconvex penalties and DC programming G Gasso, A Rakotomamonjy, S Canu IEEE Transactions on Signal Processing 57 (12), 4686-4698, 2009 | 330 | 2009 |
| Histogram of gradients of time–frequency representations for audio scene classification A Rakotomamonjy, G Gasso IEEE/ACM Transactions on Audio, Speech, and Language Processing 23 (1), 142-153, 2014 | 208 | 2014 |
| Optimizing AUC with support vector machine (SVM) A Rakotomamonjy Proceedings of European Conference on Artificial Intelligence Workshop on …, 2004 | 207* | 2004 |
| A pedestrian detector using histograms of oriented gradients and a support vector machine classifier M Bertozzi, A Broggi, M Del Rose, M Felisa, A Rakotomamonjy, F Suard Intelligent Transportation Systems Conference, 2007. ITSC 2007. IEEE, 143-148, 2007 | 172 | 2007 |
| Joint Distribution Optimal Transportation for Domain Adaptation N Courty, R Flamary, A Habrard, A Rakotomamonjy Advances in Neural Information Processing Systems, 2017 | 163 | 2017 |
| Surveying and comparing simultaneous sparse approximation (or group-lasso) algorithms A Rakotomamonjy Signal processing 91 (7), 1505-1526, 2011 | 158 | 2011 |
| Composite kernel learning M Szafranski, Y Grandvalet, A Rakotomamonjy Proceedings of the 25th international conference on Machine learning, 1040-1047, 2008 | 154 | 2008 |
| Ensemble of SVMs for improving brain computer interface P300 speller performances A Rakotomamonjy, V Guigue, G Mallet, V Alvarado Artificial Neural Networks: Biological Inspirations–ICANN 2005, 45-50, 2005 | 136 | 2005 |
| Support vector machines with a reject option Y Grandvalet, A Rakotomamonjy, J Keshet, S Canu Proceedings of the 22nd Annual Conference on Neural Information Processing …, 2008 | 107 | 2008 |
| Frames, Reproducing Kernels, Regularization and Learning. A Rakotomamonjy, S Canu, A Smola Journal of Machine Learning Research 6 (9), 2005 | 107 | 2005 |
| Automatic feature learning for spatio-spectral image classification with sparse SVM D Tuia, M Volpi, M Dalla Mura, A Rakotomamonjy, R Flamary IEEE Transactions on Geoscience and Remote Sensing 52 (10), 6062-6074, 2014 | 83 | 2014 |
| \ell_p-\ell_q penalty for sparse linear and sparse multiple kernel multi-task learning A Rakotomamonjy, Flamary, G R. and Gasso, S Canu IEEE Transactions on Neural Networks 22 (8), 1307-1320, 2011 | 80 | 2011 |
Stéphane CanuProfessor of Data Science, INSA Rouen確認したメール アドレス: insa-rouen.fr
