Rodolphe Jenatton

75 papers A* 21A 2Journal 46Unranked 5

Year	Rank	Type	Title / Venue / Authors
2024	A*	`conf`	Pi-DUAL: Using privileged information to distinguish clean from noisy labels. ICML Ke Wang, Guillermo Ortiz-Jiménez, Rodolphe Jenatton, Mark Collier, Efi Kokiopoulou, Pascal Frossard
2023	A*	`conf`	Massively Scaling Heteroscedastic Classifiers. ICLR Mark Collier, Rodolphe Jenatton, Basil Mustafa, Neil Houlsby, Jesse Berent, Effrosyni Kokiopoulou
2023	J	`jnl`	Massively Scaling Heteroscedastic Classifiers. CoRR Mark Collier, Rodolphe Jenatton, Basil Mustafa, Neil Houlsby, Jesse Berent, Effrosyni Kokiopoulou
2023	J	`jnl`	Pi-DUAL: Using Privileged Information to Distinguish Clean from Noisy Labels. CoRR Ke Wang, Guillermo Ortiz-Jiménez, Rodolphe Jenatton, Mark Collier, Efi Kokiopoulou, Pascal Frossard
2023	A*	`conf`	Scaling Vision Transformers to 22 Billion Parameters. ICML 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
2023	J	`jnl`	Scaling Vision Transformers to 22 Billion Parameters. CoRR 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 Nader Vasconcelos, Yi Tay, Thomas Mensink, Alexander Kolesnikov, Filip Pavetic, Dustin Tran, Thomas Kipf, Mario Lucic, Xiaohua Zhai, Daniel Keysers, Jeremiah Harmsen, Neil Houlsby
2023	A*	`conf`	Three Towers: Flexible Contrastive Learning with Pretrained Image Models. NeurIPS Jannik Kossen, Mark Collier, Basil Mustafa, Xiao Wang, Xiaohua Zhai, Lucas Beyer, Andreas Steiner, Jesse Berent, Rodolphe Jenatton, Effrosyni Kokiopoulou
2023	J	`jnl`	Three Towers: Flexible Contrastive Learning with Pretrained Image Models. CoRR Jannik Kossen, Mark Collier, Basil Mustafa, Xiao Wang, Xiaohua Zhai, Lucas Beyer, Andreas Steiner, Jesse Berent, Rodolphe Jenatton, Efi Kokiopoulou
2023	J	`jnl`	When does Privileged Information Explain Away Label Noise? CoRR Guillermo Ortiz-Jiménez, Mark Collier, Anant Nawalgaria, Alexander D'Amour, Jesse Berent, Rodolphe Jenatton, Effrosyni Kokiopoulou
2023	A*	`conf`	When does Privileged information Explain Away Label Noise? ICML Guillermo Ortiz-Jiménez, Mark Collier, Anant Nawalgaria, Alexander Nicholas D'Amour, Jesse Berent, Rodolphe Jenatton, Efi Kokiopoulou
2022	J	`jnl`	Deep Classifiers with Label Noise Modeling and Distance Awareness. Trans. Mach. Learn. Res. Vincent Fortuin, Mark Collier, Florian Wenzel, James Urquhart Allingham, Jeremiah Zhe Liu, Dustin Tran, Balaji Lakshminarayanan, Jesse Berent, Rodolphe Jenatton, Effrosyni Kokiopoulou
2022	A*	`conf`	Multimodal Contrastive Learning with LIMoE: the Language-Image Mixture of Experts. NeurIPS Basil Mustafa, Carlos Riquelme, Joan Puigcerver, Rodolphe Jenatton, Neil Houlsby
2022	J	`jnl`	Multimodal Contrastive Learning with LIMoE: the Language-Image Mixture of Experts. CoRR Basil Mustafa, Carlos Riquelme, Joan Puigcerver, Rodolphe Jenatton, Neil Houlsby
2022	J	`jnl`	On Mixup Regularization. J. Mach. Learn. Res. Luigi Carratino, Moustapha Cissé, Rodolphe Jenatton, Jean-Philippe Vert
2022	A*	`conf`	On the Adversarial Robustness of Mixture of Experts. NeurIPS Joan Puigcerver, Rodolphe Jenatton, Carlos Riquelme, Pranjal Awasthi, Srinadh Bhojanapalli
2022	J	`jnl`	On the Adversarial Robustness of Mixture of Experts. CoRR Joan Puigcerver, Rodolphe Jenatton, Carlos Riquelme, Pranjal Awasthi, Srinadh Bhojanapalli
2022	J	`jnl`	Plex: Towards Reliability using Pretrained Large Model Extensions. CoRR 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
2022	A	`conf`	Predicting the utility of search spaces for black-box optimization: a simple, budget-aware approach. AISTATS Setareh Ariafar, Justin Gilmer, Zachary Nado, Jasper Snoek, Rodolphe Jenatton, George E. Dahl
2022	J	`jnl`	Sparse MoEs meet Efficient Ensembles. Trans. Mach. Learn. Res. 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
2022	A*	`conf`	Transfer and Marginalize: Explaining Away Label Noise with Privileged Information. ICML Mark Collier, Rodolphe Jenatton, Effrosyni Kokiopoulou, Jesse Berent
2022	J	`jnl`	Transfer and Marginalize: Explaining Away Label Noise with Privileged Information. CoRR Mark Collier, Rodolphe Jenatton, Efi Kokiopoulou, Jesse Berent
2021	A*	`conf`	Amazon SageMaker Automatic Model Tuning: Scalable Gradient-Free Optimization. KDD 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
2021	A*	`conf`	Correlated Input-Dependent Label Noise in Large-Scale Image Classification. CVPR Mark Collier, Basil Mustafa, Efi Kokiopoulou, Rodolphe Jenatton, Jesse Berent
2021	J	`jnl`	Correlated Input-Dependent Label Noise in Large-Scale Image Classification. CoRR Mark Collier, Basil Mustafa, Efi Kokiopoulou, Rodolphe Jenatton, Jesse Berent
2021	J	`jnl`	Deep Classifiers with Label Noise Modeling and Distance Awareness. CoRR Vincent Fortuin, Mark Collier, Florian Wenzel, James Urquhart Allingham, Jeremiah Z. Liu, Dustin Tran, Balaji Lakshminarayanan, Jesse Berent, Rodolphe Jenatton, Effrosyni Kokiopoulou
2021	J	`jnl`	Predicting the utility of search spaces for black-box optimization: a simple, budget-aware approach. CoRR Setareh Ariafar, Justin Gilmer, Zachary Nado, Jasper Snoek, Rodolphe Jenatton, George E. Dahl
2021	A*	`conf`	Scaling Vision with Sparse Mixture of Experts. NeurIPS Carlos Riquelme, Joan Puigcerver, Basil Mustafa, Maxim Neumann, Rodolphe Jenatton, André Susano Pinto, Daniel Keysers, Neil Houlsby
2021	J	`jnl`	Scaling Vision with Sparse Mixture of Experts. CoRR Carlos Riquelme, Joan Puigcerver, Basil Mustafa, Maxim Neumann, Rodolphe Jenatton, André Susano Pinto, Daniel Keysers, Neil Houlsby
2021	J	`jnl`	Sparse MoEs meet Efficient Ensembles. CoRR 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
2021	A*	`conf`	Training independent subnetworks for robust prediction. ICLR Marton Havasi, Rodolphe Jenatton, Stanislav Fort, Jeremiah Zhe Liu, Jasper Snoek, Balaji Lakshminarayanan, Andrew Mingbo Dai, Dustin Tran
2021	J	`jnl`	Uncertainty Baselines: Benchmarks for Uncertainty & Robustness in Deep Learning. CoRR 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
2020	J	`jnl`	Amazon SageMaker Automatic Model Tuning: Scalable Black-box Optimization. CoRR 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
2020	J	`jnl`	Amazon SageMaker Autopilot: a white box AutoML solution at scale. CoRR 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
2020	A*	`conf`	How Good is the Bayes Posterior in Deep Neural Networks Really? ICML Florian Wenzel, Kevin Roth, Bastiaan S. Veeling, Jakub Swiatkowski, Linh Tran, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin
2020	J	`jnl`	How Good is the Bayes Posterior in Deep Neural Networks Really? CoRR Florian Wenzel, Kevin Roth, Bastiaan S. Veeling, Jakub Swiatkowski, Linh Tran, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin
2020	J	`jnl`	Hydra: Preserving Ensemble Diversity for Model Distillation. CoRR Linh Tran, Bastiaan S. Veeling, Kevin Roth, Jakub Swiatkowski, Joshua V. Dillon, Jasper Snoek, Stephan Mandt, Tim Salimans, Sebastian Nowozin, Rodolphe Jenatton
2020	A*	`conf`	Hyperparameter Ensembles for Robustness and Uncertainty Quantification. NeurIPS Florian Wenzel, Jasper Snoek, Dustin Tran, Rodolphe Jenatton
2020	J	`jnl`	Hyperparameter Ensembles for Robustness and Uncertainty Quantification. CoRR Florian Wenzel, Jasper Snoek, Dustin Tran, Rodolphe Jenatton
2020	J	`jnl`	On Mixup Regularization. CoRR Luigi Carratino, Moustapha Cissé, Rodolphe Jenatton, Jean-Philippe Vert
2020	A*	`conf`	The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks. ICML Jakub Swiatkowski, Kevin Roth, Bastiaan S. Veeling, Linh Tran, Joshua V. Dillon, Jasper Snoek, Stephan Mandt, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin
2020	J	`jnl`	The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks. CoRR Jakub Swiatkowski, Kevin Roth, Bastiaan S. Veeling, Linh Tran, Joshua V. Dillon, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin
2020	J	`jnl`	Training independent subnetworks for robust prediction. CoRR Marton Havasi, Rodolphe Jenatton, Stanislav Fort, Jeremiah Zhe Liu, Jasper Snoek, Balaji Lakshminarayanan, Andrew M. Dai, Dustin Tran
2019	J	`jnl`	Constrained Bayesian Optimization with Max-Value Entropy Search. CoRR Valerio Perrone, Iaroslav Shcherbatyi, Rodolphe Jenatton, Cédric Archambeau, Matthias W. Seeger
2019	J	`jnl`	Learning search spaces for Bayesian optimization: Another view of hyperparameter transfer learning. CoRR Valerio Perrone, Huibin Shen, Matthias W. Seeger, Cédric Archambeau, Rodolphe Jenatton
2018	A*	`conf`	Scalable Hyperparameter Transfer Learning. NeurIPS Valerio Perrone, Rodolphe Jenatton, Matthias W. Seeger, Cédric Archambeau
2017	A*	`conf`	Bayesian Optimization with Tree-structured Dependencies. ICML Rodolphe Jenatton, Cédric Archambeau, Javier González, Matthias W. Seeger
2016	A*	`conf`	Adaptive Algorithms for Online Convex Optimization with Long-term Constraints. ICML Rodolphe Jenatton, Jim C. Huang, Cédric Archambeau
2016	A*	`conf`	Online Dual Decomposition for Performance and Delivery-Based Distributed Ad Allocation. KDD Jim C. Huang, Rodolphe Jenatton, Cédric Archambeau
2016	J	`jnl`	Online optimization and regret guarantees for non-additive long-term constraints. CoRR Rodolphe Jenatton, Jim C. Huang, Cédric Archambeau
2015	J	`jnl`	Adaptive Algorithms for Online Convex Optimization with Long-term Constraints. CoRR Rodolphe Jenatton, Jim C. Huang, Cédric Archambeau
2015	J	`jnl`	Convex Relaxations for Permutation Problems. SIAM J. Matrix Anal. Appl. Fajwel Fogel, Rodolphe Jenatton, Francis R. Bach, Alexandre d'Aspremont
2015	A*	`conf`	One-Pass Ranking Models for Low-Latency Product Recommendations. KDD Antonino Freno, Martin Saveski, Rodolphe Jenatton, Cédric Archambeau
2015	J	`jnl`	Sample Complexity of Dictionary Learning and Other Matrix Factorizations. IEEE Trans. Inf. Theory Rémi Gribonval, Rodolphe Jenatton, Francis R. Bach, Martin Kleinsteuber, Matthias Seibert
2015	J	`jnl`	Sparse and Spurious: Dictionary Learning With Noise and Outliers. IEEE Trans. Inf. Theory Rémi Gribonval, Rodolphe Jenatton, Francis R. Bach
2014	—	`conf`	On the sample complexity of sparse dictionary learning. SSP Matthias Seibert, Martin Kleinsteuber, Rémi Gribonval, Rodolphe Jenatton, Francis R. Bach
2014	J	`jnl`	Sparse and spurious: dictionary learning with noise and outliers. CoRR Rémi Gribonval, Rodolphe Jenatton, Francis R. Bach
2013	—	`conf`	Convex Relaxations for Permutation Problems. NIPS Fajwel Fogel, Rodolphe Jenatton, Francis R. Bach, Alexandre d'Aspremont
2013	J	`jnl`	Sample Complexity of Dictionary Learning and other Matrix Factorizations. CoRR Rémi Gribonval, Rodolphe Jenatton, Francis R. Bach, Martin Kleinsteuber, Matthias Seibert
2012	—	`conf`	A latent factor model for highly multi-relational data. NIPS Rodolphe Jenatton, Nicolas Le Roux, Antoine Bordes, Guillaume Obozinski
2012	J	`jnl`	Local stability and robustness of sparse dictionary learning in the presence of noise CoRR Rodolphe Jenatton, Rémi Gribonval, Francis R. Bach
2012	J	`jnl`	Multiscale Mining of fMRI Data with Hierarchical Structured Sparsity. SIAM J. Imaging Sci. Rodolphe Jenatton, Alexandre Gramfort, Vincent Michel, Guillaume Obozinski, Evelyn Eger, Francis R. Bach, Bertrand Thirion
2012	J	`jnl`	Optimization with Sparsity-Inducing Penalties. Found. Trends Mach. Learn. Francis R. Bach, Rodolphe Jenatton, Julien Mairal, Guillaume Obozinski
2011	J	`jnl`	Convex and Network Flow Optimization for Structured Sparsity CoRR Julien Mairal, Rodolphe Jenatton, Guillaume Obozinski, Francis R. Bach
2011	J	`jnl`	Convex and Network Flow Optimization for Structured Sparsity. J. Mach. Learn. Res. Julien Mairal, Rodolphe Jenatton, Guillaume Obozinski, Francis R. Bach
2011	J	`jnl`	Learning Hierarchical and Topographic Dictionaries with Structured Sparsity CoRR Julien Mairal, Rodolphe Jenatton, Guillaume Obozinski, Francis R. Bach
2011	—	`conf`	Multi-scale Mining of fMRI Data with Hierarchical Structured Sparsity. PRNI Rodolphe Jenatton, Alexandre Gramfort, Vincent Michel, Guillaume Obozinski, Francis R. Bach, Bertrand Thirion
2011	J	`jnl`	Optimization with Sparsity-Inducing Penalties CoRR Francis R. Bach, Rodolphe Jenatton, Julien Mairal, Guillaume Obozinski
2011	J	`jnl`	Proximal Methods for Hierarchical Sparse Coding. J. Mach. Learn. Res. Rodolphe Jenatton, Julien Mairal, Guillaume Obozinski, Francis R. Bach
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
2011	J	`jnl`	Structured Variable Selection with Sparsity-Inducing Norms. J. Mach. Learn. Res. Rodolphe Jenatton, Jean-Yves Audibert, Francis R. Bach
2011	J	`jnl`	Structured sparsity through convex optimization CoRR Francis R. Bach, Rodolphe Jenatton, Julien Mairal, Guillaume Obozinski
2010	J	`jnl`	Network Flow Algorithms for Structured Sparsity CoRR Julien Mairal, Rodolphe Jenatton, Guillaume Obozinski, Francis R. Bach
2010	—	`conf`	Network Flow Algorithms for Structured Sparsity. NIPS Julien Mairal, Rodolphe Jenatton, Guillaume Obozinski, Francis R. Bach
2010	A*	`conf`	Proximal Methods for Sparse Hierarchical Dictionary Learning. ICML Rodolphe Jenatton, Julien Mairal, Guillaume Obozinski, Francis R. Bach
2010	A	`conf`	Structured Sparse Principal Component Analysis. AISTATS Rodolphe Jenatton, Guillaume Obozinski, Francis R. Bach