Active Bibliography

STRUCTURED PRIORS FOR SUPERVISED LEARNING IN COMPUTATIONAL BIOLOGY – Docteur De, Supérieure Des, Mines De Paris, Laurent Jacob, M. Didier, Rognan Université, M. Francis, Bach Inria, École Normale, Supérieure Examinateur, Vert Mines, Paristech Examinateur, Copyright Laurent Jacob
3 Structured Sparsity through Convex Optimization – Francis Bach, Rodolphe Jenatton, Julien Mairal, Guillaume Obozinski
2. Function space / normRegularizations – Francis Bach, Special Thanks To R. Jenatton, J. Mairal, G. Obozinski Supervised Learning, Data Xi X, Yi Y, Function Space Norm - 2009
97 Structured variable selection with sparsity-inducing norms – Rodolphe Jenatton, Jean-yves Audibert, Francis Bach, Bin Yu - 904
• Specifity: exchanges between theory / algorithms / applications – Francis Bach, Unsupervised Learning, Function Space Norm
26 SUPPORT UNION RECOVERY IN HIGH-DIMENSIONAL MULTIVARIATE REGRESSION – Guillaume Obozinski, Martin J. Wainwright, Michael I. Jordan - 2010
Submitted to the Annals of Statistics SUPPORT UNION RECOVERY IN HIGH-DIMENSIONAL MULTIVARIATE REGRESSION ∗ – Guillaume Obozinski, Martin J. Wainwright, Michael I. Jordan
7 Group Lasso with Overlaps: the Latent Group Lasso approach – Guillaume Obozinski, Sierra Inria, Ecole Normale Supérieure, Inserm U - 2011
37 Optimization with sparsity-inducing penalties – C F. Bach, R. Jenatton, J. Mairal, G. Obozinski, Francis Bach, Rodolphe Jenatton, Julien Mairal, Guillaume Obozinski - 2010
18 High-Dimensional Non-Linear Variable Selection through Hierarchical Kernel Learning – Francis Bach - 2009
Minimum Description Length Penalization for Group and Multi-Task Sparse Learning – Paramveer S. Dhillon, Dean P. Foster, Lyle H. Ungar, Francis Bach
24 Union support recovery in high-dimensional multivariate – Guillaume Obozinski, Martin J. Wainwright, Michael I. Jordan - 2008
47 SLEP: Sparse Learning with Efficient Projections – Jun Liu, Shuiwang Ji, Jieping Ye - 2010
1 Model-Consistent Sparse Estimation through the Bootstrap – Francis Bach - 2009
Structured Estimation In High-Dimensions – Sahand N Negahban, Sahand N. Negahban, Sahand N. Negahban
10 On the ℓ1-ℓq Regularized Regression – Han Liu, Jian Zhang - 2008
74 A unified framework for high-dimensional analysis of M-estimators with decomposable regularizers – Sahand Negahban, Pradeep Ravikumar, Martin J. Wainwright, Bin Yu
Learning with Sparsity: . . . – Xi Chen - 2011
Learning with Sparsity: Structures, . . . – Xi Chen - 2011