Rodolphe Jenatton's homepage

Rodolphe Jenatton

Postdoctoral researcher at Ecole Polytechnique since December 2011

CMAP, UMR CNRS 7641,
Ecole Polytechnique,
91128, Palaiseau, France.

E-mail: rodolphe [dot] jenatton [at] inria [dot] fr

I have just finished my Ph.D which I conducted within the Sierra Team, which belongs to the LIENS and the Département d'Informatique of École Normale Supérieure. It was funded by INRIA. I had the chance to be co-supervised by Francis Bach and Jean-Yves Audibert. I am now a postdoctoral researcher with Alexandre d'Aspremont within the CMAP located at Ecole Polytechnique.

(2011) R. Jenatton^*, J. Mairal^*, G. Obozinski, F. Bach (^*Contributed equally). Proximal Methods for Hierarchical Sparse Coding. Journal of Machine Learning Research, 12(Jul):2297-2334. [pdf]
(2011) J. Mairal^*, R. Jenatton^*, G. Obozinski, F. Bach (^*Contributed equally). Convex and Network Flow Optimization for Structured Sparsity. Journal of Machine Learning Research, 12(Sep):2681-2720. [pdf]
(2011) R. Jenatton, J.-Y. Audibert and F. Bach. Structured Variable Selection with Sparsity-Inducing Norms. Journal of Machine Learning Research, 12(Oct):2777-2824. [pdf] [code]

Structured Sparsity-Inducing Norms: Statistical and Algorithmic Properties with Applications to Neuroimaging.

(2011) F. Bach, R. Jenatton, J. Mairal and G. Obozinski. Convex Optimization with Sparsity-Inducing Norms. In S. Sra, S. Nowozin, S. J. Wright., editors, Optimization for Machine Learning, MIT Press, 2011. [pdf]

(2010) J. Mairal^*, R. Jenatton^*, G. Obozinski, F. Bach (^*Contributed equally). Network Flow Algorithms for Structured Sparsity. Advances in Neural Information Processing Systems (NIPS). [pdf] [pdf (Arxiv technical report)] [code]
(2010) R. Jenatton^*, J. Mairal^*, G. Obozinski, F. Bach (^*Contributed equally). Proximal Methods for Sparse Hierarchical Dictionary Learning. International Conference on Machine Learning (ICML). [pdf] [appendix] [code] [bib]
(2010) R. Jenatton, G. Obozinski, F. Bach. Structured Sparse Principal Component Analysis. International Conference on Artificial Intelligence and Statistics (AISTATS). [pdf] [code] [bib]

(2011) F. Bach, R. Jenatton, J. Mairal and G. Obozinski. Optimization with Sparsity-Inducing Penalties. Technical report, submitted. [pdf (Arxiv technical report)]
(2011) R. Jenatton, A. Gramfort, V. Michel, G. Obozinski, E. Eger, F. Bach and B. Thirion. Multi-scale Mining of fMRI Data with Hierarchical Structured Sparsity. Technical report, submitted. [pdf (HAL technical report)]
(2011) J. Mairal^*, R. Jenatton^*, G. Obozinski, F. Bach (^*Contributed equally). Convex and Network Flow Optimization for Structured Sparsity. Technical report, submitted. [pdf (Arxiv technical report)]
(2010) R. Jenatton^*, J. Mairal^*, G. Obozinski, F. Bach (^*Contributed equally). Proximal Methods for Hierarchical Sparse Coding. Technical report, submitted. [pdf (HAL technical report)] [code]
(2009) R. Jenatton, G. Obozinski and F. Bach. Structured Sparse Principal Component Analysis. Technical report. [pdf (Arxiv technical report)] [bib]
(2009) R. Jenatton, J.-Y. Audibert and F. Bach. Structured Variable Selection with Sparsity-Inducing Norms. Technical report. [pdf (Arxiv technical report)] [code] [bib]

(2011) R. Jenatton, A. Gramfort, V. Michel, G. Obozinski, F. Bach and B. Thirion. Multi-scale Mining of fMRI Data with Hierarchical Structured Sparsity. International Workshop on Pattern Recognition in Neuroimaging (PRNI).
(2010) G. Varoquaux, R. Jenatton, A. Gramfort, G. Obozinski, B. Thirion and F. Bach. Sparse Structured Dictionary Learning for Brain Resting-State Activity Modeling. NIPS Workshop on Practical Applications of Sparse Modeling: Open Issues and New Directions.
(2009) R. Jenatton, J.-Y. Audibert and F. Bach. Active Set Algorithm for Structured Sparsity-Inducing Norms. OPT 2009: 2nd NIPS Workshop on Optimization for Machine Learning. [pdf] [slide] [video]

Last modification : December 29th 2011.