Rodolphe Jenatton

According to our database, Rodolphe Jenatton authored at least 52 papers between 2010 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

Pi-DUAL: Using Privileged Information to Distinguish Clean from Noisy Labels.

Ke Wang, Guillermo Ortiz-Jiménez, Rodolphe Jenatton, Mark Collier, Efi Kokiopoulou, Pascal Frossard

CoRR, 2023

Three Towers: Flexible Contrastive Learning with Pretrained Image Models.

Jannik Kossen, Mark Collier, Basil Mustafa, Xiao Wang, Xiaohua Zhai, Lucas Beyer, Andreas Steiner, Jesse Berent, Rodolphe Jenatton, Efi Kokiopoulou

CoRR, 2023

Scaling Vision Transformers to 22 Billion Parameters.

Mostafa Dehghani, Josip Djolonga, Basil Mustafa, Piotr Padlewski, Jonathan Heek, Justin Gilmer, Andreas Steiner, Mathilde Caron, Robert Geirhos, Ibrahim Alabdulmohsin, Rodolphe Jenatton, Lucas Beyer, Michael Tschannen, Anurag Arnab, Xiao Wang, Carlos Riquelme, Matthias Minderer, Joan Puigcerver, Utku Evci, Manoj Kumar, Sjoerd van Steenkiste, Gamaleldin F. Elsayed, Aravindh Mahendran, Fisher Yu, Avital Oliver, Fantine Huot, Jasmijn Bastings, Mark Patrick Collier, Alexey A. Gritsenko, Vighnesh Birodkar, Cristina N. Vasconcelos, Yi Tay, Thomas Mensink, Alexander Kolesnikov, Filip Pavetic, Dustin Tran, Thomas Kipf, Mario Lucic, Xiaohua Zhai, Daniel Keysers, Jeremiah Harmsen, Neil Houlsby

CoRR, 2023

Three Towers: Flexible Contrastive Learning with Pretrained Image Models.

Jannik Kossen, Mark Collier, Basil Mustafa, Xiao Wang, Xiaohua Zhai, Lucas Beyer, Andreas Steiner, Jesse Berent, Rodolphe Jenatton, Effrosyni Kokiopoulou

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

When does Privileged information Explain Away Label Noise?

Guillermo Ortiz-Jiménez, Mark Collier, Anant Nawalgaria, Alexander Nicholas D'Amour, Jesse Berent, Rodolphe Jenatton, Efi Kokiopoulou

Proceedings of the International Conference on Machine Learning, 2023

Scaling Vision Transformers to 22 Billion Parameters.

Mostafa Dehghani, Josip Djolonga, Basil Mustafa, Piotr Padlewski, Jonathan Heek, Justin Gilmer, Andreas Peter Steiner, Mathilde Caron, Robert Geirhos, Ibrahim Alabdulmohsin, Rodolphe Jenatton, Lucas Beyer, Michael Tschannen, Anurag Arnab, Xiao Wang, Carlos Riquelme Ruiz, Matthias Minderer, Joan Puigcerver, Utku Evci, Manoj Kumar, Sjoerd van Steenkiste, Gamaleldin Fathy Elsayed, Aravindh Mahendran, Fisher Yu, Avital Oliver, Fantine Huot, Jasmijn Bastings, Mark Collier, Alexey A. Gritsenko, Vighnesh Birodkar, Cristina Nader Vasconcelos, Yi Tay, Thomas Mensink, Alexander Kolesnikov, Filip Pavetic, Dustin Tran, Thomas Kipf, Mario Lucic, Xiaohua Zhai, Daniel Keysers, Jeremiah J. Harmsen, Neil Houlsby

Proceedings of the International Conference on Machine Learning, 2023

Massively Scaling Heteroscedastic Classifiers.

Mark Collier, Rodolphe Jenatton, Basil Mustafa, Neil Houlsby, Jesse Berent, Effrosyni Kokiopoulou

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Deep Classifiers with Label Noise Modeling and Distance Awareness.

Vincent Fortuin, Mark Collier, Florian Wenzel, James Urquhart Allingham, Jeremiah Zhe Liu, Dustin Tran, Balaji Lakshminarayanan, Jesse Berent, Rodolphe Jenatton, Effrosyni Kokiopoulou

Trans. Mach. Learn. Res., 2022

Sparse MoEs meet Efficient Ensembles.

James Urquhart Allingham, Florian Wenzel, Zelda E. Mariet, Basil Mustafa, Joan Puigcerver, Neil Houlsby, Ghassen Jerfel, Vincent Fortuin, Balaji Lakshminarayanan, Jasper Snoek, Dustin Tran, Carlos Riquelme Ruiz, Rodolphe Jenatton

Trans. Mach. Learn. Res., 2022

On Mixup Regularization.

Luigi Carratino, Moustapha Cissé, Rodolphe Jenatton, Jean-Philippe Vert

J. Mach. Learn. Res., 2022

Plex: Towards Reliability using Pretrained Large Model Extensions.

Dustin Tran, Jeremiah Z. Liu, Michael W. Dusenberry, Du Phan, Mark Collier, Jie Ren, Kehang Han, Zi Wang, Zelda Mariet, Huiyi Hu, Neil Band, Tim G. J. Rudner, Karan Singhal, Zachary Nado, Joost van Amersfoort, Andreas Kirsch, Rodolphe Jenatton, Nithum Thain, Honglin Yuan, Kelly Buchanan, Kevin Murphy, D. Sculley, Yarin Gal, Zoubin Ghahramani, Jasper Snoek, Balaji Lakshminarayanan

CoRR, 2022

On the Adversarial Robustness of Mixture of Experts.

Joan Puigcerver, Rodolphe Jenatton, Carlos Riquelme, Pranjal Awasthi, Srinadh Bhojanapalli

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Multimodal Contrastive Learning with LIMoE: the Language-Image Mixture of Experts.

Basil Mustafa, Carlos Riquelme, Joan Puigcerver, Rodolphe Jenatton, Neil Houlsby

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Transfer and Marginalize: Explaining Away Label Noise with Privileged Information.

Mark Collier, Rodolphe Jenatton, Effrosyni Kokiopoulou, Jesse Berent

Proceedings of the International Conference on Machine Learning, 2022

Predicting the utility of search spaces for black-box optimization: a simple, budget-aware approach.

Setareh Ariafar, Justin Gilmer, Zachary Nado, Jasper Snoek, Rodolphe Jenatton, George E. Dahl

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Uncertainty Baselines: Benchmarks for Uncertainty & Robustness in Deep Learning.

Zachary Nado, Neil Band, Mark Collier, Josip Djolonga, Michael W. Dusenberry, Sebastian Farquhar, Angelos Filos, Marton Havasi, Rodolphe Jenatton, Ghassen Jerfel, Jeremiah Z. Liu, Zelda Mariet, Jeremy Nixon, Shreyas Padhy, Jie Ren, Tim G. J. Rudner, Yeming Wen, Florian Wenzel, Kevin Murphy, D. Sculley, Balaji Lakshminarayanan, Jasper Snoek, Yarin Gal, Dustin Tran

CoRR, 2021

Scaling Vision with Sparse Mixture of Experts.

Carlos Riquelme, Joan Puigcerver, Basil Mustafa, Maxim Neumann, Rodolphe Jenatton, André Susano Pinto, Daniel Keysers, Neil Houlsby

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Amazon SageMaker Automatic Model Tuning: Scalable Gradient-Free Optimization.

Valerio Perrone, Huibin Shen, Aida Zolic, Iaroslav Shcherbatyi, Amr Ahmed, Tanya Bansal, Michele Donini, Fela Winkelmolen, Rodolphe Jenatton, Jean Baptiste Faddoul, Barbara Pogorzelska, Miroslav Miladinovic, Krishnaram Kenthapadi, Matthias W. Seeger, Cédric Archambeau

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Training independent subnetworks for robust prediction.

Marton Havasi, Rodolphe Jenatton, Stanislav Fort, Jeremiah Zhe Liu, Jasper Snoek, Balaji Lakshminarayanan, Andrew Mingbo Dai, Dustin Tran

Proceedings of the 9th International Conference on Learning Representations, 2021

Correlated Input-Dependent Label Noise in Large-Scale Image Classification.

Mark Collier, Basil Mustafa, Efi Kokiopoulou, Rodolphe Jenatton, Jesse Berent

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020

Amazon SageMaker Automatic Model Tuning: Scalable Black-box Optimization.

Valerio Perrone, Huibin Shen, Aida Zolic, Iaroslav Shcherbatyi, Amr Ahmed, Tanya Bansal, Michele Donini, Fela Winkelmolen, Rodolphe Jenatton, Jean Baptiste Faddoul, Barbara Pogorzelska, Miroslav Miladinovic, Krishnaram Kenthapadi, Matthias W. Seeger, Cédric Archambeau

CoRR, 2020

Amazon SageMaker Autopilot: a white box AutoML solution at scale.

Piali Das, Valerio Perrone, Nikita Ivkin, Tanya Bansal, Zohar S. Karnin, Huibin Shen, Iaroslav Shcherbatyi, Yotam Elor, Wilton Wu, Aida Zolic, Thibaut Liénart, Alex Tang, Amr Ahmed, Jean Baptiste Faddoul, Rodolphe Jenatton, Fela Winkelmolen, Philip Gautier, Leo Dirac, Andre Perunicic, Miroslav Miladinovic, Giovanni Zappella, Cédric Archambeau, Matthias W. Seeger, Bhaskar Dutt, Laurence Rouesnel

CoRR, 2020

Hydra: Preserving Ensemble Diversity for Model Distillation.

Linh Tran, Bastiaan S. Veeling, Kevin Roth, Jakub Swiatkowski, Joshua V. Dillon, Jasper Snoek, Stephan Mandt, Tim Salimans, Sebastian Nowozin, Rodolphe Jenatton

CoRR, 2020

Hyperparameter Ensembles for Robustness and Uncertainty Quantification.

Florian Wenzel, Jasper Snoek, Dustin Tran, Rodolphe Jenatton

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

How Good is the Bayes Posterior in Deep Neural Networks Really?

Florian Wenzel, Kevin Roth, Bastiaan S. Veeling, Jakub Swiatkowski, Linh Tran, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin

Proceedings of the 37th International Conference on Machine Learning, 2020

The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks.

Jakub Swiatkowski, Kevin Roth, Bastiaan S. Veeling, Linh Tran, Joshua V. Dillon, Jasper Snoek, Stephan Mandt, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Constrained Bayesian Optimization with Max-Value Entropy Search.

Valerio Perrone, Iaroslav Shcherbatyi, Rodolphe Jenatton, Cédric Archambeau, Matthias W. Seeger

CoRR, 2019

Learning search spaces for Bayesian optimization: Another view of hyperparameter transfer learning.

Valerio Perrone, Huibin Shen, Matthias W. Seeger, Cédric Archambeau, Rodolphe Jenatton

CoRR, 2019

2018

Scalable Hyperparameter Transfer Learning.

Valerio Perrone, Rodolphe Jenatton, Matthias W. Seeger, Cédric Archambeau

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017

Bayesian Optimization with Tree-structured Dependencies.

Rodolphe Jenatton, Cédric Archambeau, Javier González, Matthias W. Seeger

Proceedings of the 34th International Conference on Machine Learning, 2017

2016

Online optimization and regret guarantees for non-additive long-term constraints.

Rodolphe Jenatton, Jim C. Huang, Cédric Archambeau

CoRR, 2016

Online Dual Decomposition for Performance and Delivery-Based Distributed Ad Allocation.

Jim C. Huang, Rodolphe Jenatton, Cédric Archambeau

Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

Adaptive Algorithms for Online Convex Optimization with Long-term Constraints.

Rodolphe Jenatton, Jim C. Huang, Cédric Archambeau

Proceedings of the 33nd International Conference on Machine Learning, 2016

2015

Sample Complexity of Dictionary Learning and Other Matrix Factorizations.

Rémi Gribonval, Rodolphe Jenatton, Francis R. Bach, Martin Kleinsteuber, Matthias Seibert

IEEE Trans. Inf. Theory, 2015

Sparse and Spurious: Dictionary Learning With Noise and Outliers.

Rémi Gribonval, Rodolphe Jenatton, Francis R. Bach

IEEE Trans. Inf. Theory, 2015

Convex Relaxations for Permutation Problems.

Fajwel Fogel, Rodolphe Jenatton, Francis R. Bach, Alexandre d'Aspremont

SIAM J. Matrix Anal. Appl., 2015

One-Pass Ranking Models for Low-Latency Product Recommendations.

Antonino Freno, Martin Saveski, Rodolphe Jenatton, Cédric Archambeau

Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

2014

On the sample complexity of sparse dictionary learning.

Matthias Seibert, Martin Kleinsteuber, Rémi Gribonval, Rodolphe Jenatton, Francis R. Bach

Proceedings of the IEEE Workshop on Statistical Signal Processing, 2014

2012

Multiscale Mining of fMRI Data with Hierarchical Structured Sparsity.

Rodolphe Jenatton, Alexandre Gramfort, Vincent Michel, Guillaume Obozinski, Evelyn Eger, Francis R. Bach, Bertrand Thirion

SIAM J. Imaging Sci., 2012

Optimization with Sparsity-Inducing Penalties.

Francis R. Bach, Rodolphe Jenatton, Julien Mairal, Guillaume Obozinski

Found. Trends Mach. Learn., 2012

Local stability and robustness of sparse dictionary learning in the presence of noise

Rodolphe Jenatton, Rémi Gribonval, Francis R. Bach

CoRR, 2012

A latent factor model for highly multi-relational data.

Rodolphe Jenatton, Nicolas Le Roux, Antoine Bordes, Guillaume Obozinski

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

2011

Structured Sparsity-Inducing Norms : Statistical and Algorithmic Properties with Applications to Neuroimaging. (Normes Parcimonieuses Structurées : Propriétés Statistiques et Algorithmiques avec Applications à l'Imagerie Cérébrale).

Rodolphe Jenatton

PhD thesis, 2011

Convex and Network Flow Optimization for Structured Sparsity.

Julien Mairal, Rodolphe Jenatton, Guillaume Obozinski, Francis R. Bach

J. Mach. Learn. Res., 2011

Proximal Methods for Hierarchical Sparse Coding.

Rodolphe Jenatton, Julien Mairal, Guillaume Obozinski, Francis R. Bach

J. Mach. Learn. Res., 2011

Structured Variable Selection with Sparsity-Inducing Norms.

Rodolphe Jenatton, Jean-Yves Audibert, Francis R. Bach

J. Mach. Learn. Res., 2011

Learning Hierarchical and Topographic Dictionaries with Structured Sparsity

Julien Mairal, Rodolphe Jenatton, Guillaume Obozinski, Francis R. Bach

CoRR, 2011

Structured sparsity through convex optimization

Francis R. Bach, Rodolphe Jenatton, Julien Mairal, Guillaume Obozinski

CoRR, 2011

Multi-scale Mining of fMRI Data with Hierarchical Structured Sparsity.

Rodolphe Jenatton, Alexandre Gramfort, Vincent Michel, Guillaume Obozinski, Francis R. Bach, Bertrand Thirion

Proceedings of the 2011 International Workshop on Pattern Recognition in NeuroImaging, 2011

2010

Structured Sparse Principal Component Analysis.

Rodolphe Jenatton, Guillaume Obozinski, Francis R. Bach

Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Network Flow Algorithms for Structured Sparsity.

Julien Mairal, Rodolphe Jenatton, Guillaume Obozinski, Francis R. Bach

Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Proximal Methods for Sparse Hierarchical Dictionary Learning.

Rodolphe Jenatton, Julien Mairal, Guillaume Obozinski, Francis R. Bach

Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010