| Optimization with sparsity-inducing penalties F Bach, R Jenatton, J Mairal, G Obozinski Foundations and Trends in Machine Learning 4 (1), 1-106, 2012 | 1370 | 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 | 1177 | 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 | 591 | 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 | 531 | 2012 |
| Proximal methods for sparse hierarchical dictionary learning. R Jenatton, J Mairal, G Obozinski, FR Bach ICML 1, 2, 2010 | 476 | 2010 |
| Canonical tensor decomposition for knowledge base completion T Lacroix, N Usunier, G Obozinski International Conference on Machine Learning, 2869-2878, 2018 | 475 | 2018 |
| Multi-task feature selection G Obozinski, B Taskar, M Jordan Statistics Department, UC Berkeley, Tech. Rep 2 (2.2), 2, 2006 | 462 | 2006 |
| Support union recovery in high-dimensional multivariate regression G Obozinski, MJ Wainwright, MI Jordan | 453* | 2011 |
| Structured sparsity through convex optimization F Bach, R Jenatton, J Mairal, G Obozinski Statistical Science 27 (4), 450-468, 2012 | 427 | 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 | 414 | 2010 |
| Structured sparse principal component analysis R Jenatton, G Obozinski, F Bach International Conference on Artificial Intelligence and Statistics, 2010 | 402 | 2010 |
| Convex optimization with sparsity-inducing norms F Bach, R Jenatton, J Mairal, G Obozinski Optimization for Machine Learning, 2011 | 376 | 2011 |
| Tensor Decompositions for temporal knowledge base completion T Lacroix, G Obozinski, N Usunier International Conference on Learning Representations, 2020 | 331 | 2020 |
| 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 | 319 | 2009 |
| 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, 1-19, 2008 | 304 | 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 | 237 | 2011 |
| Group lasso with overlaps: the latent group lasso approach G Obozinski, L Jacob, JP Vert arXiv preprint arXiv:1110.0413, 2011 | 236 | 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 | 204 | 2010 |
| 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 | 187 | 2012 |
| Empirical Bayes Transductive Meta-Learning with Synthetic Gradients SX Hu, PG Moreno, Y Xiao, X Shen, G Obozinski, ND Lawrence, ... International Conference on Learning Representations, 2020 | 182 | 2020 |
Francis BachInria - Ecole Normale Supérieure在 inria.fr 的電子郵件地址已通過驗證
