| Optimization with sparsity-inducing penalties F Bach, R Jenatton, J Mairal, G Obozinski arXiv preprint arXiv:1108.0775, 2011 | 1025 | 2011 |
| Structured variable selection with sparsity-inducing norms R Jenatton, JY Audibert, F Bach Journal of Machine Learning Research 12, 2777-2824, 2011 | 595 | 2011 |
| Optimization for machine learning S Sra, S Nowozin, SJ Wright Mit Press, 2012 | 548 | 2012 |
| Proximal methods for sparse hierarchical dictionary learning R Jenatton, J Mairal, G Obozinski, FR Bach ICML, 2010 | 448 | 2010 |
| A latent factor model for highly multi-relational data R Jenatton, N Le Roux, A Bordes, G Obozinski Advances in Neural Information Processing Systems 25 (NIPS 2012), 3176-3184, 2012 | 389 | 2012 |
| Proximal methods for hierarchical sparse coding R Jenatton, J Mairal, G Obozinski, F Bach Journal of Machine Learning Research, 2297-2334, 2011 | 362 | 2011 |
| Convex optimization with sparsity-inducing norms F Bach, R Jenatton, J Mairal, G Obozinski Optimization for Machine Learning 5, 19-53, 2011 | 344 | 2011 |
| Structured sparsity through convex optimization F Bach, R Jenatton, J Mairal, G Obozinski Statistical Science 27 (4), 450-468, 2012 | 334 | 2012 |
| Structured sparse principal component analysis R Jenatton, G Obozinski, F Bach International Conference on Artificial Intelligence and Statistics (AISTATS), 2010 | 330 | 2010 |
| Network flow algorithms for structured sparsity J Mairal, R Jenatton, G Obozinski, F Bach Advances in Neural Information Processing Systems (NIPS), 2010 | 184 | 2010 |
| Multiscale mining of fMRI data with hierarchical structured sparsity R Jenatton, A Gramfort, V Michel, G Obozinski, E Eger, F Bach, B Thirion SIAM Journal on Imaging Sciences 5 (3), 835-856, 2012 | 110 | 2012 |
| Convex and Network Flow Optimization for Structured Sparsity. J Mairal, R Jenatton, G Obozinski, F Bach Journal of Machine Learning Research 12 (9), 2011 | 100 | 2011 |
| Convex relaxations for permutation problems F Fogel, R Jenatton, F Bach, A d'Aspremont arXiv preprint arXiv:1306.4805, 2013 | 89 | 2013 |
| Sparse and spurious: dictionary learning with noise and outliers R Gribonval, R Jenatton, F Bach IEEE Transactions on Information Theory 61 (11), 6298-6319, 2015 | 86 | 2015 |
| Sample complexity of dictionary learning and other matrix factorizations R Gribonval, R Jenatton, F Bach, M Kleinsteuber, M Seibert IEEE Transactions on Information Theory 61 (6), 3469-3486, 2015 | 85 | 2015 |
| Adaptive algorithms for online convex optimization with long-term constraints R Jenatton, J Huang, C Archambeau International Conference on Machine Learning, 402-411, 2016 | 66 | 2016 |
| Scalable hyperparameter transfer learning V Perrone, R Jenatton, M Seeger, C Archambeau Proceedings of the 32nd International Conference on Neural Information …, 2018 | 52 | 2018 |
| Local stability and robustness of sparse dictionary learning in the presence of noise R Jenatton, R Gribonval, F Bach arXiv preprint arXiv:1210.0685, 2012 | 46 | 2012 |
| How good is the bayes posterior in deep neural networks really? F Wenzel, K Roth, BS Veeling, J Świątkowski, L Tran, S Mandt, J Snoek, ... arXiv preprint arXiv:2002.02405, 2020 | 37 | 2020 |
| Bayesian optimization with tree-structured dependencies R Jenatton, C Archambeau, J González, M Seeger International Conference on Machine Learning, 1655-1664, 2017 | 37 | 2017 |
Francis BachInria - Ecole Normale SupérieureVerified email at inria.fr
