| Optimization with sparsity-inducing penalties F Bach, R Jenatton, J Mairal, G Obozinski Foundations and Trends in Machine Learning 4 (1), 1-106, 2012 | 966 | 2012 |
| Group lasso with overlap and graph lasso L Jacob, G Obozinski, JP Vert Proceedings of the 26th annual international conference on machine learning …, 2009 | 917 | 2009 |
| Joint covariate selection and joint subspace selection for multiple classification problems G Obozinski, B Taskar, MI Jordan Statistics and Computing 20 (2), 231-252, 2010 | 495 | 2010 |
| Proximal methods for sparse hierarchical dictionary learning R Jenatton, J Mairal, G Obozinski, FR Bach ICML, 2010 | 426 | 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, 3176-3184, 2012 | 368 | 2012 |
| Proximal methods for hierarchical sparse coding R Jenatton, J Mairal, G Obozinski, F Bach Journal of Machine Learning Research 12 (Jul), 2297-2334, 2010 | 348 | 2010 |
| Multi-task feature selection G Obozinski, B Taskar, M Jordan Statistics Department, UC Berkeley, Tech. Rep 2 (2.2), 2, 2006 | 345 | 2006 |
| Convex optimization with sparsity-inducing norms F Bach, R Jenatton, J Mairal, G Obozinski Optimization for Machine Learning, 2011 | 332 | 2011 |
| Support union recovery in high-dimensional multivariate regression G Obozinski, MJ Wainwright, MI Jordan The Annals of Statistics 39 (1), 1-47, 2011 | 331* | 2011 |
| Structured sparse principal component analysis R Jenatton, G Obozinski, F Bach International Conference on Artificial Intelligence and Statistics, 2010 | 320 | 2010 |
| Structured sparsity through convex optimization F Bach, R Jenatton, J Mairal, G Obozinski Statistical Science 27 (4), 450-468, 2012 | 309 | 2012 |
| A critical assessment of Mus musculusgene function prediction using integrated genomic evidence L Peña-Castillo, M Tasan, CL Myers, H Lee, T Joshi, C Zhang, Y Guan, ... Genome biology 9 (S1), S2, 2008 | 270 | 2008 |
| Trace Lasso: a trace norm regularization for correlated designs E Grave, G Obozinski, F Bach Advances in Neural Information Processing Systems 24, 2187-2195, 2011 | 182 | 2011 |
| Network flow algorithms for structured sparsity J Mairal, R Jenatton, G Obozinski, F Bach Advances in Neural Information Processing Systems 23, 1558-1566, 2010 | 178 | 2010 |
| Genomic privacy and limits of individual detection in a pool S Sankararaman, G Obozinski, MI Jordan, E Halperin Nature genetics 41 (9), 965-967, 2009 | 177 | 2009 |
| Group lasso with overlaps: the latent group lasso approach G Obozinski, L Jacob, JP Vert arXiv preprint arXiv:1110.0413, 2011 | 160 | 2011 |
| On the equivalence between herding and conditional gradient algorithms F Bach, S Lacoste-Julien, G Obozinski Proceedings of the 29th International Conference on Machine Learning, 1359--1366, 2012 | 110 | 2012 |
| Consistent probabilistic outputs for protein function prediction G Obozinski, G Lanckriet, C Grant, MI Jordan, WS Noble Genome Biology 9 (S1), S6, 2008 | 110 | 2008 |
| Multi-scale mining of fMRI data with hierarchical structured sparsity R Jenatton, A Gramfort, V Michel, G Obozinski, F Bach, B Thirion SIAM Journal on Imaging Sciences 5 (3), 835--856, 2012 | 105 | 2012 |
| Canonical tensor decomposition for knowledge base completion T Lacroix, N Usunier, G Obozinski International Conference on Machine Learning, 2869-2878, 2018 | 99 | 2018 |
Francis BachInria - Ecole Normale SupérieureAdresse e-mail validée de inria.fr
