← Authors

Rodolphe Jenatton

27 papers · 2010–2024 · 6 conferences · across top CS/AI conferences

Achievements

πŸƒ Academic Marathon (14) 🧭 Keyword Pioneer 🌈 Renaissance Researcher (6) 🌍 Conference Polyglot (6) πŸŒ‰ Interdisciplinary Bridge 🐝 Cross-Pollinator (8) 🐣 Hot Topic Early Bird πŸ—ΊοΈ Taxonomy Completionist (21) πŸ‘₯ Mega-Team (42) πŸ‘‘ Triple Crown πŸ”¬ Deep Specialist (11) πŸ† Keyword Champion πŸ’Ž Century Club (27) ⚑ Prolific Year (5) πŸš€ Conference Pioneer πŸ“ˆ Trend Setter ❓ The Questioner (2) πŸ”₯ Unstoppable (9) πŸ—ƒοΈ Keyword Collector (120)

Conferences

NIPS (10) ICML (8) JMLR (4) AISTATS (2) ICLR (2) CVPR (1)

Top co-authors

Mark Collier (7) Basil Mustafa (6) Jasper Snoek (5) Francis Bach (5) Jesse Berent (5) Neil Houlsby (4) Joan Puigcerver (4) CΓ©dric Archambeau (4) Efi Kokiopoulou (3) Effrosyni Kokiopoulou (3)

Keywords

hyperparameter optimization (4) image classification (4) neural network (4) mixture of expert (3) structured sparsity (3) bayesian optimization (3) dictionary learning (3) label noise (3) lipschitz constant (2) privileged information (2) proximal operator (2) vision transformer (2) sparsity-inducing norms (2) black-box optimization (2) network flow (2) convex optimization (2) contrastive learning (2) uncertainty quantification (2) transfer learning (2) gaussian process (2)

Papers

Pi-DUAL: Using privileged information to distinguish clean from noisy labels ICML 2024
Massively Scaling Heteroscedastic Classifiers ICLR 2023
When does Privileged information Explain Away Label Noise? ICML 2023
Scaling Vision Transformers to 22 Billion Parameters ICML 2023
Three Towers: Flexible Contrastive Learning with Pretrained Image Models NIPS 2023
Transfer and Marginalize: Explaining Away Label Noise with Privileged Information ICML 2022
On Mixup Regularization JMLR 2022
Predicting the utility of search spaces for black-box optimization: a simple, budget-aware approach AISTATS 2022
Multimodal Contrastive Learning with LIMoE: the Language-Image Mixture of Experts NIPS 2022
On the Adversarial Robustness of Mixture of Experts NIPS 2022
Training independent subnetworks for robust prediction ICLR 2021
Scaling Vision with Sparse Mixture of Experts NIPS 2021
Correlated Input-Dependent Label Noise in Large-Scale Image Classification CVPR 2021
The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks ICML 2020
Hyperparameter Ensembles for Robustness and Uncertainty Quantification NIPS 2020
How Good is the Bayes Posterior in Deep Neural Networks Really? ICML 2020
Learning search spaces for Bayesian optimization: Another view of hyperparameter transfer learning NIPS 2019
Scalable Hyperparameter Transfer Learning NIPS 2018
Bayesian Optimization with Tree-structured Dependencies ICML 2017
Adaptive Algorithms for Online Convex Optimization with Long-term Constraints ICML 2016
Convex Relaxations for Permutation Problems NIPS 2013
A latent factor model for highly multi-relational data NIPS 2012
Proximal Methods for Hierarchical Sparse Coding JMLR 2011
Convex and Network Flow Optimization for Structured Sparsity JMLR 2011
Structured Variable Selection with Sparsity-Inducing Norms JMLR 2011
Structured Sparse Principal Component Analysis AISTATS 2010
Network Flow Algorithms for Structured Sparsity NIPS 2010