Rodolphe JENATTON
Rodolphe JENATTON
Senior machine learning scientist at Google Brain, Berlin
Verified email at google.com - Homepage
Title
Cited by
Cited by
Year
Optimization with sparsity-inducing penalties
F Bach, R Jenatton, J Mairal, G Obozinski
arXiv preprint arXiv:1108.0775, 2011
10402011
Structured variable selection with sparsity-inducing norms
R Jenatton, JY Audibert, F Bach
Journal of Machine Learning Research 12, 2777-2824, 2011
6002011
Optimization for machine learning
S Sra, S Nowozin, SJ Wright
Mit Press, 2012
5602012
Proximal methods for sparse hierarchical dictionary learning
R Jenatton, J Mairal, G Obozinski, FR Bach
ICML, 2010
4492010
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
3962012
Proximal methods for hierarchical sparse coding
R Jenatton, J Mairal, G Obozinski, F Bach
Journal of Machine Learning Research, 2297-2334, 2011
3632011
Convex optimization with sparsity-inducing norms
F Bach, R Jenatton, J Mairal, G Obozinski
Optimization for Machine Learning 5, 19-53, 2011
3462011
Structured sparsity through convex optimization
F Bach, R Jenatton, J Mairal, G Obozinski
Statistical Science 27 (4), 450-468, 2012
3362012
Structured sparse principal component analysis
R Jenatton, G Obozinski, F Bach
International Conference on Artificial Intelligence and Statistics (AISTATS), 2010
3352010
Network flow algorithms for structured sparsity
J Mairal, R Jenatton, G Obozinski, F Bach
Advances in Neural Information Processing Systems (NIPS), 2010
1832010
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
1112012
Convex and Network Flow Optimization for Structured Sparsity.
J Mairal, R Jenatton, G Obozinski, F Bach
Journal of Machine Learning Research 12 (9), 2011
1002011
Convex relaxations for permutation problems
F Fogel, R Jenatton, F Bach, A d'Aspremont
arXiv preprint arXiv:1306.4805, 2013
912013
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
882015
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
852015
Adaptive algorithms for online convex optimization with long-term constraints
R Jenatton, J Huang, C Archambeau
International Conference on Machine Learning, 402-411, 2016
722016
Scalable hyperparameter transfer learning
V Perrone, R Jenatton, M Seeger, C Archambeau
Proceedings of the 32nd International Conference on Neural Information …, 2018
572018
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
472020
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
462012
Bayesian optimization with tree-structured dependencies
R Jenatton, C Archambeau, J González, M Seeger
International Conference on Machine Learning, 1655-1664, 2017
382017
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Articles 1–20