Jenatton, Rodolphe

33 publications

ICML 2024 Pi-DUAL: Using Privileged Information to Distinguish Clean from Noisy Labels Ke Wang, Guillermo Ortiz-Jimenez, Rodolphe Jenatton, Mark Collier, Efi Kokiopoulou, Pascal Frossard

ICLR 2023 Massively Scaling Heteroscedastic Classifiers Mark Collier, Rodolphe Jenatton, Basil Mustafa, Neil Houlsby, Jesse Berent, Effrosyni Kokiopoulou

ICML 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

NeurIPS 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

ICMLW 2023 Three Towers: Flexible Contrastive Learning with Pretrained Image Models Jannik Kossen, Mark Collier, Basil Mustafa, Xiao Wang, Xiaohua Zhai, Lucas Beyer, Andreas Peter Steiner, Jesse Berent, Rodolphe Jenatton, Efi Kokiopoulou

ICML 2023 When Does Privileged Information Explain Away Label Noise? Guillermo Ortiz-Jimenez, Mark Collier, Anant Nawalgaria, Alexander Nicholas D’Amour, Jesse Berent, Rodolphe Jenatton, Efi Kokiopoulou

AISTATS 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 Dahl

TMLR 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

NeurIPS 2022 Multimodal Contrastive Learning with LIMoE: The Language-Image Mixture of Experts Basil Mustafa, Carlos Riquelme, Joan Puigcerver, Rodolphe Jenatton, Neil Houlsby

JMLR 2022 On Mixup Regularization Luigi Carratino, Moustapha Cissé, Rodolphe Jenatton, Jean-Philippe Vert

NeurIPS 2022 On the Adversarial Robustness of Mixture of Experts Joan Puigcerver, Rodolphe Jenatton, Carlos Riquelme, Pranjal Awasthi, Srinadh Bhojanapalli

ICMLW 2022 Plex: Towards Reliability Using Pretrained Large Model Extensions Dustin Tran, Jeremiah Zhe Liu, Michael W Dusenberry, Du Phan, Mark Collier, Jie Ren, Kehang Han, Zi Wang, Zelda E Mariet, Huiyi Hu, Neil Band, Tim G. J. Rudner, Karan Singhal, Zachary Nado, Joost van Amersfoort, Andreas Kirsch, Rodolphe Jenatton, Nithum Thain, Honglin Yuan, E. Kelly Buchanan, Kevin Patrick Murphy, D. Sculley, Yarin Gal, Zoubin Ghahramani, Jasper Snoek, Balaji Lakshminarayanan

TMLR 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

ICML 2022 Transfer and Marginalize: Explaining Away Label Noise with Privileged Information Mark Collier, Rodolphe Jenatton, Effrosyni Kokiopoulou, Jesse Berent

CVPR 2021 Correlated Input-Dependent Label Noise in Large-Scale Image Classification Mark Collier, Basil Mustafa, Efi Kokiopoulou, Rodolphe Jenatton, Jesse Berent

NeurIPS 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

ICLR 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

ICML 2020 How Good Is the Bayes Posterior in Deep Neural Networks Really? Florian Wenzel, Kevin Roth, Bastiaan Veeling, Jakub Swiatkowski, Linh Tran, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin

NeurIPS 2020 Hyperparameter Ensembles for Robustness and Uncertainty Quantification Florian Wenzel, Jasper Snoek, Dustin Tran, Rodolphe Jenatton

ICML 2020 The K-Tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks Jakub Swiatkowski, Kevin Roth, Bastiaan Veeling, Linh Tran, Joshua Dillon, Jasper Snoek, Stephan Mandt, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin

NeurIPS 2019 Learning Search Spaces for Bayesian Optimization: Another View of Hyperparameter Transfer Learning Valerio Perrone, Huibin Shen, Matthias W Seeger, Cedric Archambeau, Rodolphe Jenatton

NeurIPS 2018 Scalable Hyperparameter Transfer Learning Valerio Perrone, Rodolphe Jenatton, Matthias W Seeger, Cedric Archambeau

ICML 2017 Bayesian Optimization with Tree-Structured Dependencies Rodolphe Jenatton, Cedric Archambeau, Javier González, Matthias Seeger

ICML 2016 Adaptive Algorithms for Online Convex Optimization with Long-Term Constraints Rodolphe Jenatton, Jim Huang, Cedric Archambeau

NeurIPS 2013 Convex Relaxations for Permutation Problems Fajwel Fogel, Rodolphe Jenatton, Francis Bach, Alexandre D'Aspremont

NeurIPS 2012 A Latent Factor Model for Highly Multi-Relational Data Rodolphe Jenatton, Nicolas L. Roux, Antoine Bordes, Guillaume R. Obozinski

FnTML 2012 Optimization with Sparsity-Inducing Penalties Francis R. Bach, Rodolphe Jenatton, Julien Mairal, Guillaume Obozinski

JMLR 2011 Convex and Network Flow Optimization for Structured Sparsity Julien Mairal, Rodolphe Jenatton, Guillaume Obozinski, Francis Bach

JMLR 2011 Proximal Methods for Hierarchical Sparse Coding Rodolphe Jenatton, Julien Mairal, Guillaume Obozinski, Francis Bach

JMLR 2011 Structured Variable Selection with Sparsity-Inducing Norms Rodolphe Jenatton, Jean-Yves Audibert, Francis Bach

NeurIPS 2010 Network Flow Algorithms for Structured Sparsity Julien Mairal, Rodolphe Jenatton, Francis R. Bach, Guillaume R. Obozinski

ICML 2010 Proximal Methods for Sparse Hierarchical Dictionary Learning Rodolphe Jenatton, Julien Mairal, Guillaume Obozinski, Francis R. Bach

AISTATS 2010 Structured Sparse Principal Component Analysis Rodolphe Jenatton, Guillaume Obozinski, Francis Bach