| SimpleMKL A Rakotomamonjy, FR Bach, S Canu, Y Grandvalet Journal of Machine Learning Research 9 (Nov), 2491-2521, 2008 | 1470 | 2008 |
| Semi-supervised learning by entropy minimization Y Grandvalet, Y Bengio Advances in neural information processing systems, 529-536, 2005 | 666 | 2005 |
| No unbiased estimator of the variance of k-fold cross-validation Y Bengio, Y Grandvalet Journal of machine learning research 5 (Sep), 1089-1105, 2004 | 637 | 2004 |
| Svm and kernel methods matlab toolbox S Canu http://asi. insa-rouen. fr/enseignants/~ arakoto/toolbox/index. html, 2005 | 523 | 2005 |
| 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 | 331 | 2007 |
| Adaptive scaling for feature selection in SVMs Y Grandvalet, S Canu Advances in neural information processing systems, 569-576, 2003 | 225 | 2003 |
| Composite kernel learning M Szafranski, Y Grandvalet, A Rakotomamonjy Machine learning 79 (1-2), 73-103, 2010 | 131 | 2010 |
| Least absolute shrinkage is equivalent to quadratic penalization Y Grandvalet International Conference on Artificial Neural Networks, 201-206, 1998 | 128 | 1998 |
| Bagging equalizes influence Y Grandvalet Machine Learning 55 (3), 251-270, 2004 | 119 | 2004 |
| Noise injection: Theoretical prospects Y Grandvalet, S Canu, S Boucheron Neural Computation 9 (5), 1093-1108, 1997 | 102 | 1997 |
| Semi-supervised MarginBoost. F d'Alché-Buc, Y Grandvalet, C Ambroise NIPS, 553-560, 2001 | 99 | 2001 |
| Outcomes of the equivalence of adaptive ridge with least absolute shrinkage Y Grandvalet, S Canu Advances in neural information processing systems, 445-451, 1999 | 84 | 1999 |
| Support vector machines with a reject option Y Grandvalet, A Rakotomamonjy, J Keshet, S Canu Advances in neural information processing systems, 537-544, 2009 | 82 | 2009 |
| Optimizing F-measures by cost-sensitive classification SP Parambath, N Usunier, Y Grandvalet Advances in Neural Information Processing Systems, 2123-2131, 2014 | 77 | 2014 |
| Inferring multiple graphical structures J Chiquet, Y Grandvalet, C Ambroise Statistics and Computing 21 (4), 537-553, 2011 | 76 | 2011 |
| Comments on" Noise injection into inputs in back propagation learning" Y Grandvalet, S Canu IEEE Transactions on Systems, Man, and Cybernetics 25 (4), 678-681, 1995 | 51 | 1995 |
| A probabilistic interpretation of SVMs with an application to unbalanced classification Y Grandvalet, J Mariéthoz, S Bengio Advances in Neural Information Processing Systems, 467-474, 2006 | 48 | 2006 |
| Resample and combine: an approach to improving uncertainty representation in evidential pattern classification J François, Y Grandvalet, T Denoeux, JM Roger Information Fusion 4 (2), 75-85, 2003 | 45 | 2003 |
| Combining two and three-way embedding models for link prediction in knowledge bases A García-Durán, A Bordes, N Usunier, Y Grandvalet Journal of Artificial Intelligence Research 55, 715-742, 2016 | 43 | 2016 |
| A coverage-based approach to recommendation diversity on similarity graph SA Puthiya Parambath, N Usunier, Y Grandvalet Proceedings of the 10th ACM Conference on Recommender Systems, 15-22, 2016 | 42 | 2016 |
Stéphane CanuProfessor of Data Science, INSA RouenAdresse e-mail validée de insa-rouen.fr
