| Gene networks inference using dynamic Bayesian networks BE Perrin, L Ralaivola, A Mazurie, S Bottani, J Mallet, F d'Alché-Buc Bioinformatics-Oxford 19 (2), 138-148, 2003 | 630 | 2003 |
| Graph kernels for chemical informatics L Ralaivola, SJ Swamidass, H Saigo, P Baldi Neural networks 18 (8), 1093-1110, 2005 | 613 | 2005 |
| Kernels for small molecules and the prediction of mutagenicity, toxicity and anti-cancer activity SJ Swamidass, J Chen, J Bruand, P Phung, L Ralaivola, P Baldi Bioinformatics 21 (suppl_1), i359-i368, 2005 | 254 | 2005 |
| Incremental support vector machine learning: A local approach L Ralaivola, F d’Alché-Buc Artificial Neural Networks—ICANN 2001: International Conference Vienna …, 2001 | 175 | 2001 |
| The pharmacophore kernel for virtual screening with support vector machines P Mahé, L Ralaivola, V Stoven, JP Vert Journal of chemical information and modeling 46 (5), 2003-2014, 2006 | 128 | 2006 |
| Dynamic screening: Accelerating first-order algorithms for the lasso and group-lasso A Bonnefoy, V Emiya, L Ralaivola, R Gribonval IEEE Transactions on Signal Processing 63 (19), 5121-5132, 2015 | 99 | 2015 |
| Learning SVMs from sloppily labeled data G Stempfel, L Ralaivola Artificial Neural Networks–ICANN 2009: 19th International Conference …, 2009 | 96 | 2009 |
| One-to four-dimensional kernels for virtual screening and the prediction of physical, chemical, and biological properties CA Azencott, A Ksikes, SJ Swamidass, JH Chen, L Ralaivola, P Baldi Journal of chemical information and modeling 47 (3), 965-974, 2007 | 88 | 2007 |
| Chromatic PAC-Bayes bounds for non-iid data: Applications to ranking and stationary β-mixing processes L Ralaivola, M Szafranski, G Stempfel The Journal of Machine Learning Research 11, 1927-1956, 2010 | 86 | 2010 |
| Time series filtering, smoothing and learning using the kernel Kalman filter L Ralaivola, F d'Alché-Buc Proceedings. 2005 IEEE International Joint Conference on Neural Networks …, 2005 | 83 | 2005 |
| Dynamical modeling with kernels for nonlinear time series prediction L Ralaivola, F d'Alché-Buc Advances in neural information processing systems 16, 2003 | 78 | 2003 |
| Grammatical inference as a principal component analysis problem R Bailly, F Denis, L Ralaivola Proceedings of the 26th Annual International Conference on Machine Learning …, 2009 | 77 | 2009 |
| A dynamic screening principle for the lasso A Bonnefoy, V Emiya, L Ralaivola, R Gribonval 2014 22nd European signal processing conference (EUSIPCO), 6-10, 2014 | 71 | 2014 |
| Multiple indefinite kernel learning with mixed norm regularization M Kowalski, M Szafranski, L Ralaivola Proceedings of the 26th Annual International Conference on Machine Learning …, 2009 | 62 | 2009 |
| Empirical Bernstein inequalities for u-statistics T Peel, S Anthoine, L Ralaivola Advances in Neural Information Processing Systems 23, 2010 | 56 | 2010 |
| Graph-based inter-subject pattern analysis of fMRI data S Takerkart, G Auzias, B Thirion, L Ralaivola PloS one 9 (8), e104586, 2014 | 37 | 2014 |
| PAC-Bayesian generalization bound on confusion matrix for multi-class classification E Morvant, S Koço, L Ralaivola arXiv preprint arXiv:1202.6228, 2012 | 35 | 2012 |
| SVM and pattern-enriched common fate graphs for the game of go. L Ralaivola, L Wu, P Baldi ESANN 2005, 27-29, 2005 | 31 | 2005 |
| Confusion matrix stability bounds for multiclass classification P Machart, L Ralaivola arXiv preprint arXiv:1202.6221, 2012 | 29 | 2012 |
| Quantum bandits B Casalé, G Di Molfetta, H Kadri, L Ralaivola Quantum Machine Intelligence 2, 1-7, 2020 | 27 | 2020 |
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