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Rodolphe JENATTON
Rodolphe JENATTON
Senior machine learning scientist at Google Brain, Berlin
Adresse e-mail validée de google.com - Page d'accueil
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Optimization with sparsity-inducing penalties
F Bach, R Jenatton, J Mairal, G Obozinski
Foundations and Trends® in Machine Learning 4 (1), 1-106, 2012
12172012
Structured variable selection with sparsity-inducing norms
R Jenatton, JY Audibert, F Bach
Journal of Machine Learning Research 12, 2777-2824, 2011
6512011
A latent factor model for highly multi-relational data
R Jenatton, N Roux, A Bordes, GR Obozinski
Advances in neural information processing systems 25, 2012
4892012
Proximal methods for sparse hierarchical dictionary learning.
R Jenatton, J Mairal, G Obozinski, FR Bach
ICML 1, 2, 2010
4652010
Proximal methods for hierarchical sparse coding
R Jenatton, J Mairal, G Obozinski, F Bach
Journal of Machine Learning Research, 2297-2334, 2011
3942011
Structured sparsity through convex optimization
F Bach, R Jenatton, J Mairal, G Obozinski
3832012
Structured sparse principal component analysis
R Jenatton, G Obozinski, F Bach
International Conference on Artificial Intelligence and Statistics (AISTATS), 2010
3812010
Convex optimization with sparsity-inducing norms
F Bach, R Jenatton, J Mairal, G Obozinski
Optimization for Machine Learning 5, 19-53, 2011
3672011
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
2692020
Network flow algorithms for structured sparsity
J Mairal, R Jenatton, G Obozinski, F Bach
Advances in Neural Information Processing Systems (NIPS), 2010
1942010
Scaling vision with sparse mixture of experts
C Riquelme, J Puigcerver, B Mustafa, M Neumann, R Jenatton, ...
Advances in Neural Information Processing Systems 34, 8583-8595, 2021
1672021
Scalable hyperparameter transfer learning
V Perrone, R Jenatton, MW Seeger, C Archambeau
Advances in neural information processing systems 31, 2018
1402018
Hyperparameter ensembles for robustness and uncertainty quantification
F Wenzel, J Snoek, D Tran, R Jenatton
Advances in Neural Information Processing Systems 33, 6514-6527, 2020
1392020
Convex relaxations for permutation problems
F Fogel, R Jenatton, F Bach, A d'Aspremont
Advances in neural information processing systems 26, 2013
1342013
Adaptive algorithms for online convex optimization with long-term constraints
R Jenatton, J Huang, C Archambeau
International Conference on Machine Learning, 402-411, 2016
1302016
Training independent subnetworks for robust prediction
M Havasi, R Jenatton, S Fort, JZ Liu, J Snoek, B Lakshminarayanan, ...
arXiv preprint arXiv:2010.06610, 2020
1252020
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
1212012
Convex and Network Flow Optimization for Structured Sparsity.
J Mairal, R Jenatton, G Obozinski, F Bach
Journal of Machine Learning Research 12 (9), 2011
1172011
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
1022015
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
972015
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