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2020 – today
- 2022
[c21]Setareh Ariafar, Justin Gilmer, Zachary Nado, Jasper Snoek, Rodolphe Jenatton, George E. Dahl:
Predicting the utility of search spaces for black-box optimization: a simple, budget-aware approach. AISTATS 2022: 11056-11071- [c20]Mark Collier, Rodolphe Jenatton, Effrosyni Kokiopoulou, Jesse Berent:
Transfer and Marginalize: Explaining Away Label Noise with Privileged Information. ICML 2022: 4219-4237 - [i29]Mark Collier, Rodolphe Jenatton, Efi Kokiopoulou, Jesse Berent:
Transfer and Marginalize: Explaining Away Label Noise with Privileged Information. CoRR abs/2202.09244 (2022) - [i28]Basil Mustafa, Carlos Riquelme, Joan Puigcerver, Rodolphe Jenatton, Neil Houlsby:
Multimodal Contrastive Learning with LIMoE: the Language-Image Mixture of Experts. CoRR abs/2206.02770 (2022) - [i27]Dustin Tran, Jeremiah 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:
Plex: Towards Reliability using Pretrained Large Model Extensions. CoRR abs/2207.07411 (2022) - 2021
- [c19]Mark Collier, Basil Mustafa, Efi Kokiopoulou, Rodolphe Jenatton, Jesse Berent:
Correlated Input-Dependent Label Noise in Large-Scale Image Classification. CVPR 2021: 1551-1560 - [c18]Marton Havasi, Rodolphe Jenatton, Stanislav Fort, Jeremiah Zhe Liu, Jasper Snoek, Balaji Lakshminarayanan, Andrew Mingbo Dai, Dustin Tran:
Training independent subnetworks for robust prediction. ICLR 2021 - [c17]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:
Amazon SageMaker Automatic Model Tuning: Scalable Gradient-Free Optimization. KDD 2021: 3463-3471 - [c16]Carlos Riquelme, Joan Puigcerver, Basil Mustafa, Maxim Neumann, Rodolphe Jenatton, André Susano Pinto, Daniel Keysers, Neil Houlsby:
Scaling Vision with Sparse Mixture of Experts. NeurIPS 2021: 8583-8595 - [i26]Mark Collier, Basil Mustafa, Efi Kokiopoulou, Rodolphe Jenatton, Jesse Berent:
Correlated Input-Dependent Label Noise in Large-Scale Image Classification. CoRR abs/2105.10305 (2021) - [i25]Zachary Nado, Neil Band, Mark Collier, Josip Djolonga, Michael W. Dusenberry, Sebastian Farquhar, Angelos Filos, Marton Havasi, Rodolphe Jenatton, Ghassen Jerfel, Jeremiah 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:
Uncertainty Baselines: Benchmarks for Uncertainty & Robustness in Deep Learning. CoRR abs/2106.04015 (2021) - [i24]Carlos Riquelme, Joan Puigcerver, Basil Mustafa, Maxim Neumann, Rodolphe Jenatton, André Susano Pinto, Daniel Keysers, Neil Houlsby:
Scaling Vision with Sparse Mixture of Experts. CoRR abs/2106.05974 (2021) - [i23]Vincent Fortuin, Mark Collier, Florian Wenzel, James Urquhart Allingham, Jeremiah Liu, Dustin Tran, Balaji Lakshminarayanan, Jesse Berent, Rodolphe Jenatton, Effrosyni Kokiopoulou:
Deep Classifiers with Label Noise Modeling and Distance Awareness. CoRR abs/2110.02609 (2021) - [i22]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:
Sparse MoEs meet Efficient Ensembles. CoRR abs/2110.03360 (2021) - [i21]Setareh Ariafar, Justin Gilmer, Zachary Nado, Jasper Snoek, Rodolphe Jenatton, George E. Dahl:
Predicting the utility of search spaces for black-box optimization: a simple, budget-aware approach. CoRR abs/2112.08250 (2021) - 2020
- [c15]Jakub Swiatkowski, Kevin Roth, Bastiaan S. Veeling, Linh Tran, Joshua V. Dillon, Jasper Snoek, Stephan Mandt, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin:
The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks. ICML 2020: 9289-9299 - [c14]Florian Wenzel, Kevin Roth, Bastiaan S. Veeling, Jakub Swiatkowski, Linh Tran, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin:
How Good is the Bayes Posterior in Deep Neural Networks Really? ICML 2020: 10248-10259 - [c13]Florian Wenzel, Jasper Snoek, Dustin Tran, Rodolphe Jenatton:
Hyperparameter Ensembles for Robustness and Uncertainty Quantification. NeurIPS 2020 - [i20]Linh Tran, Bastiaan S. Veeling, Kevin Roth, Jakub Swiatkowski, Joshua V. Dillon, Jasper Snoek, Stephan Mandt, Tim Salimans, Sebastian Nowozin, Rodolphe Jenatton:
Hydra: Preserving Ensemble Diversity for Model Distillation. CoRR abs/2001.04694 (2020) - [i19]Florian Wenzel, Kevin Roth, Bastiaan S. Veeling, Jakub Swiatkowski, Linh Tran, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin:
How Good is the Bayes Posterior in Deep Neural Networks Really? CoRR abs/2002.02405 (2020) - [i18]Jakub Swiatkowski, Kevin Roth, Bastiaan S. Veeling, Linh Tran, Joshua V. Dillon, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin:
The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks. CoRR abs/2002.02655 (2020) - [i17]Luigi Carratino, Moustapha Cissé, Rodolphe Jenatton, Jean-Philippe Vert:
On Mixup Regularization. CoRR abs/2006.06049 (2020) - [i16]Florian Wenzel, Jasper Snoek, Dustin Tran, Rodolphe Jenatton:
Hyperparameter Ensembles for Robustness and Uncertainty Quantification. CoRR abs/2006.13570 (2020) - [i15]Marton Havasi, Rodolphe Jenatton, Stanislav Fort, Jeremiah Zhe Liu, Jasper Snoek, Balaji Lakshminarayanan, Andrew M. Dai, Dustin Tran:
Training independent subnetworks for robust prediction. CoRR abs/2010.06610 (2020) - [i14]Piali Das, Valerio Perrone, Nikita Ivkin, Tanya Bansal, Zohar S. Karnin, Huibin Shen, Iaroslav Shcherbatyi, Yotam Elor, Wilton Wu, Aida Zolic, Thibaut Lienart, 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:
Amazon SageMaker Autopilot: a white box AutoML solution at scale. CoRR abs/2012.08483 (2020) - [i13]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:
Amazon SageMaker Automatic Model Tuning: Scalable Black-box Optimization. CoRR abs/2012.08489 (2020)
2010 – 2019
- 2019
- [i12]Valerio Perrone, Huibin Shen, Matthias W. Seeger, Cédric Archambeau, Rodolphe Jenatton:
Learning search spaces for Bayesian optimization: Another view of hyperparameter transfer learning. CoRR abs/1909.12552 (2019) - [i11]Valerio Perrone, Iaroslav Shcherbatyi, Rodolphe Jenatton, Cédric Archambeau, Matthias W. Seeger:
Constrained Bayesian Optimization with Max-Value Entropy Search. CoRR abs/1910.07003 (2019) - 2018
- [c12]Valerio Perrone, Rodolphe Jenatton, Matthias W. Seeger, Cédric Archambeau:
Scalable Hyperparameter Transfer Learning. NeurIPS 2018: 6846-6856 - 2017
- [c11]Rodolphe Jenatton, Cédric Archambeau, Javier González, Matthias W. Seeger:
Bayesian Optimization with Tree-structured Dependencies. ICML 2017: 1655-1664 - 2016
- [c10]Rodolphe Jenatton, Jim C. Huang, Cédric Archambeau:
Adaptive Algorithms for Online Convex Optimization with Long-term Constraints. ICML 2016: 402-411 - [c9]Jim C. Huang, Rodolphe Jenatton, Cédric Archambeau:
Online Dual Decomposition for Performance and Delivery-Based Distributed Ad Allocation. KDD 2016: 117-126 - [i10]Rodolphe Jenatton, Jim C. Huang, Cédric Archambeau:
Online optimization and regret guarantees for non-additive long-term constraints. CoRR abs/1602.05394 (2016) - 2015
- [j8]Fajwel Fogel, Rodolphe Jenatton, Francis R. Bach, Alexandre d'Aspremont:
Convex Relaxations for Permutation Problems. SIAM J. Matrix Anal. Appl. 36(4): 1465-1488 (2015) - [j7]Rémi Gribonval, Rodolphe Jenatton, Francis R. Bach, Martin Kleinsteuber, Matthias Seibert:
Sample Complexity of Dictionary Learning and Other Matrix Factorizations. IEEE Trans. Inf. Theory 61(6): 3469-3486 (2015) - [j6]Rémi Gribonval, Rodolphe Jenatton, Francis R. Bach:
Sparse and Spurious: Dictionary Learning With Noise and Outliers. IEEE Trans. Inf. Theory 61(11): 6298-6319 (2015) - [c8]Antonino Freno, Martin Saveski, Rodolphe Jenatton, Cédric Archambeau:
One-Pass Ranking Models for Low-Latency Product Recommendations. KDD 2015: 1789-1798 - [i9]Rodolphe Jenatton, Jim C. Huang, Cédric Archambeau:
Adaptive Algorithms for Online Convex Optimization with Long-term Constraints. CoRR abs/1512.07422 (2015) - 2014
- [c7]Matthias Seibert, Martin Kleinsteuber, Rémi Gribonval, Rodolphe Jenatton, Francis R. Bach:
On the sample complexity of sparse dictionary learning. SSP 2014: 244-247 - [i8]Rémi Gribonval, Rodolphe Jenatton, Francis R. Bach:
Sparse and spurious: dictionary learning with noise and outliers. CoRR abs/1407.5155 (2014) - 2013
- [c6]Fajwel Fogel, Rodolphe Jenatton, Francis R. Bach, Alexandre d'Aspremont:
Convex Relaxations for Permutation Problems. NIPS 2013: 1016-1024 - [i7]Rémi Gribonval, Rodolphe Jenatton, Francis R. Bach, Martin Kleinsteuber, Matthias Seibert:
Sample Complexity of Dictionary Learning and other Matrix Factorizations. CoRR abs/1312.3790 (2013) - 2012
- [j5]Francis R. Bach, Rodolphe Jenatton, Julien Mairal, Guillaume Obozinski:
Optimization with Sparsity-Inducing Penalties. Found. Trends Mach. Learn. 4(1): 1-106 (2012) - [j4]Rodolphe Jenatton, Alexandre Gramfort, Vincent Michel, Guillaume Obozinski, Evelyn Eger, Francis R. Bach, Bertrand Thirion:
Multiscale Mining of fMRI Data with Hierarchical Structured Sparsity. SIAM J. Imaging Sci. 5(3): 835-856 (2012) - [c5]Rodolphe Jenatton, Nicolas Le Roux, Antoine Bordes, Guillaume Obozinski:
A latent factor model for highly multi-relational data. NIPS 2012: 3176-3184 - [i6]Rodolphe Jenatton, Rémi Gribonval, Francis R. Bach:
Local stability and robustness of sparse dictionary learning in the presence of noise. CoRR abs/1210.0685 (2012) - 2011
- [b1]Rodolphe Jenatton:
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). École normale supérieure de Cachan, France, 2011 - [j3]Rodolphe Jenatton, Julien Mairal, Guillaume Obozinski, Francis R. Bach:
Proximal Methods for Hierarchical Sparse Coding. J. Mach. Learn. Res. 12: 2297-2334 (2011) - [j2]Julien Mairal, Rodolphe Jenatton, Guillaume Obozinski, Francis R. Bach:
Convex and Network Flow Optimization for Structured Sparsity. J. Mach. Learn. Res. 12: 2681-2720 (2011) - [j1]Rodolphe Jenatton, Jean-Yves Audibert, Francis R. Bach:
Structured Variable Selection with Sparsity-Inducing Norms. J. Mach. Learn. Res. 12: 2777-2824 (2011) - [c4]Rodolphe Jenatton, Alexandre Gramfort, Vincent Michel, Guillaume Obozinski, Francis R. Bach, Bertrand Thirion:
Multi-scale Mining of fMRI Data with Hierarchical Structured Sparsity. PRNI 2011: 69-72 - [i5]Julien Mairal, Rodolphe Jenatton, Guillaume Obozinski, Francis R. Bach:
Convex and Network Flow Optimization for Structured Sparsity. CoRR abs/1104.1872 (2011) - [i4]Francis R. Bach, Rodolphe Jenatton, Julien Mairal, Guillaume Obozinski:
Optimization with Sparsity-Inducing Penalties. CoRR abs/1108.0775 (2011) - [i3]Francis R. Bach, Rodolphe Jenatton, Julien Mairal, Guillaume Obozinski:
Structured sparsity through convex optimization. CoRR abs/1109.2397 (2011) - [i2]Julien Mairal, Rodolphe Jenatton, Guillaume Obozinski, Francis R. Bach:
Learning Hierarchical and Topographic Dictionaries with Structured Sparsity. CoRR abs/1110.4481 (2011) - 2010
- [c3]Rodolphe Jenatton, Julien Mairal, Guillaume Obozinski, Francis R. Bach:
Proximal Methods for Sparse Hierarchical Dictionary Learning. ICML 2010: 487-494 - [c2]Julien Mairal, Rodolphe Jenatton, Guillaume Obozinski, Francis R. Bach:
Network Flow Algorithms for Structured Sparsity. NIPS 2010: 1558-1566 - [c1]Rodolphe Jenatton, Guillaume Obozinski, Francis R. Bach:
Structured Sparse Principal Component Analysis. AISTATS 2010: 366-373 - [i1]Julien Mairal, Rodolphe Jenatton, Guillaume Obozinski, Francis R. Bach:
Network Flow Algorithms for Structured Sparsity. CoRR abs/1008.5209 (2010)
Coauthor Index
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