Language-guided Skill Learning with Temporal Variational Inference
Haotian Fu, Pratyusha Sharma, Elias Stengel-Eskin, George Konidaris, Nicolas Le Roux, Marc-Alexandre Côté, Xingdi Yuan
ICML 2024 | July 2024
Nicolas Le Roux
Sr Principal Researcher
Publications
Publication Type
-
Towards Modular LLMs by Building and Reusing a Library of LoRAs
O. Ostapenko, Zhan Su, E. Ponti, Laurent Charlin, Nicolas Le Roux, Matheus Pereira, Lucas Caccia, Alessandro Sordoni
ICML 2024 | May 2024
-
Joint Prompt Optimization of Stacked LLMs using Variational Inference
Alessandro Sordoni, Xingdi Yuan, Marc-Alexandre Côté, Matheus Pereira, Adam Trischler, Ziang Xiao, Arian Hosseini, Friederike Niedtner, Nicolas Le Roux
NeurIPS 2023 | October 2023
Multi-Head Adapter Routing for Cross-Task Generalization
Lucas Caccia, Edoardo Ponti, Zhan Su, Matheus Pereira, Nicolas Le Roux, Alessandro Sordoni
NeurIPS 2023 | October 2023
-
A general class of surrogate functions for stable and efficient reinforcement learning
Sharan Vaswani, Olivier Bachem, Simone Totaro, Robert Müller, Shivam Garg, Matthieu Geist, Marlos C. Machado, Pablo Samuel Castro, Nicolas Le Roux
2022 International Conference on Artificial Intelligence and Statistics | March 2022
On the Convergence of Stochastic Extragradient for Bilinear Games using Restarted Iteration Averaging
Chris Junchi Li, Yaodong Yu, Nicolas Loizou, Gauthier Gidel, Yi Ma, Nicolas Le Roux, Michael I. Jordan
2022 International Conference on Artificial Intelligence and Statistics | March 2022
-
Learning a Generative Model of Images by Factoring Appearance and Shape
Nicolas Le Roux, Nicolas Heess, Jamie Shotton, John Winn
Neural Computation | March 2011, Vol 23: pp. 593-650
Weakly Supervised Learning of Foreground-Background Segmentation using Masked RBMs
Nicolas Heess, Nicolas Le Roux, John Winn
International Conference on Artificial Neural Networks | January 2011
International Conference on Artificial Neural Networks
-
Avancées théoriques sur la représentation et l’optimisation des réseaux de neurones
Nicolas Le Roux, Le Roux, Nicolas
March 2008
March 2008
Learning the 2-D Topology of Images
Nicolas Le Roux, Yoshua Bengio, Pascal Lamblin, Marc Joliveau, Balázs Kégl
NIPS2007 | January 2008
Representational Power of Restricted Boltzmann Machines and Deep Belief Networks
Nicolas Le Roux, Yoshua Bengio
Neural Computation | January 2008
Topmoumoute online natural gradient algorithm
Nicolas Le Roux, Pierre-Antoine Manzagol, Yoshua Bengio
NIPS2007 | January 2008
-
Continuous Neural Networks
Nicolas Le Roux, Yoshua Bengio
AISTAT2007 | January 2007
-
Convex Neural Networks
Yoshua Bengio, Nicolas Le Roux, Pascal Vincent, Olivier Delalleau, Patrice Marcotte
Advances in Neural Information Processing Systems 18 | Publié par MIT Press | 2006 | Advances in Neural Information Processing Systems 18 edition
Label Propagation and Quadratic Criterion
Yoshua Bengio, Olivier Delalleau, Nicolas Le Roux
Semi-Supervised Learning | Publié par MIT Press | 2006 | Semi-Supervised Learning edition
Large-Scale Algorithms
Olivier Delalleau, Yoshua Bengio, Nicolas Le Roux
Semi-Supervised Learning | Publié par MIT Press | 2006 | Semi-Supervised Learning edition
Spectral Dimensionality Reduction
Yoshua Bengio, Olivier Delalleau, Nicolas Le Roux, Jean-François Paiement, Pascal Vincent, Marie Ouimet
Feature Extraction, Foundations and Applications, Spectral Dimensionality Reduction | Publié par Springer | 2006
The Curse of Highly Variable Functions for Local Kernel Machines
Yoshua Bengio, Olivier Delalleau, Nicolas Le Roux
Advances in Neural Information Processing Systems 18 | January 2006
-
The Curse of Dimensionality for Local Kernel Machines
Yoshua Bengio, Olivier Delalleau, Nicolas Le Roux
TR-1258 | March 2005
Efficient Non-Parametric Function Induction in Semi-Supervised Learning
Olivier Delalleau, Yoshua Bengio, Nicolas Le Roux
Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics | January 2005
Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics
-
Learning eigenfunctions links spectral embedding and kernel PCA
Yoshua Bengio, Olivier Delalleau, Nicolas Le Roux, Jean-François Paiement, Pascal Vincent, Marie Ouimet
Neural Computation | January 2004, Vol 16: pp. 2197-2219
Out-of-Sample Extensions for LLE, Isomap, MDS, Eigenmaps, and Spectral Clustering
Yoshua Bengio, Jean-François Paiement, Pascal Vincent, Olivier Delalleau, Nicolas Le Roux, Marie Ouimet
Advances in Neural Information Processing Systems 16 | Publié par MIT Press | 2004 | Advances in Neural Information Processing Systems 16 edition
-
Spectral Clustering and Kernel PCA are Learning Eigenfunctions
Yoshua Bengio, Pascal Vincent, Jean-François Paiement, Olivier Delalleau, Marie Ouimet, Nicolas Le Roux
1239 | January 2003
Filtre par zone de recherche
-
Language-guided Skill Learning with Temporal Variational Inference
Haotian Fu, Pratyusha Sharma, Elias Stengel-Eskin, George Konidaris, Nicolas Le Roux, Marc-Alexandre Côté, Xingdi Yuan
ICML 2024 | July 2024
Towards Modular LLMs by Building and Reusing a Library of LoRAs
O. Ostapenko, Zhan Su, E. Ponti, Laurent Charlin, Nicolas Le Roux, Matheus Pereira, Lucas Caccia, Alessandro Sordoni
ICML 2024 | May 2024
Multi-Head Adapter Routing for Cross-Task Generalization
Lucas Caccia, Edoardo Ponti, Zhan Su, Matheus Pereira, Nicolas Le Roux, Alessandro Sordoni
NeurIPS 2023 | October 2023
Joint Prompt Optimization of Stacked LLMs using Variational Inference
Alessandro Sordoni, Xingdi Yuan, Marc-Alexandre Côté, Matheus Pereira, Adam Trischler, Ziang Xiao, Arian Hosseini, Friederike Niedtner, Nicolas Le Roux
NeurIPS 2023 | October 2023
A general class of surrogate functions for stable and efficient reinforcement learning
Sharan Vaswani, Olivier Bachem, Simone Totaro, Robert Müller, Shivam Garg, Matthieu Geist, Marlos C. Machado, Pablo Samuel Castro, Nicolas Le Roux
2022 International Conference on Artificial Intelligence and Statistics | March 2022
Learning a Generative Model of Images by Factoring Appearance and Shape
Nicolas Le Roux, Nicolas Heess, Jamie Shotton, John Winn
Neural Computation | March 2011, Vol 23: pp. 593-650
-
On the Convergence of Stochastic Extragradient for Bilinear Games using Restarted Iteration Averaging
Chris Junchi Li, Yaodong Yu, Nicolas Loizou, Gauthier Gidel, Yi Ma, Nicolas Le Roux, Michael I. Jordan
2022 International Conference on Artificial Intelligence and Statistics | March 2022
Continuous Neural Networks
Nicolas Le Roux, Yoshua Bengio
AISTAT2007 | January 2007
-
Learning a Generative Model of Images by Factoring Appearance and Shape
Nicolas Le Roux, Nicolas Heess, Jamie Shotton, John Winn
Neural Computation | March 2011, Vol 23: pp. 593-650
-
Weakly Supervised Learning of Foreground-Background Segmentation using Masked RBMs
Nicolas Heess, Nicolas Le Roux, John Winn
International Conference on Artificial Neural Networks | January 2011
International Conference on Artificial Neural Networks
Topmoumoute online natural gradient algorithm
Nicolas Le Roux, Pierre-Antoine Manzagol, Yoshua Bengio
NIPS2007 | January 2008
Out-of-Sample Extensions for LLE, Isomap, MDS, Eigenmaps, and Spectral Clustering
Yoshua Bengio, Jean-François Paiement, Pascal Vincent, Olivier Delalleau, Nicolas Le Roux, Marie Ouimet
Advances in Neural Information Processing Systems 16 | Publié par MIT Press | 2004 | Advances in Neural Information Processing Systems 16 edition
-
Avancées théoriques sur la représentation et l’optimisation des réseaux de neurones
Nicolas Le Roux, Le Roux, Nicolas
March 2008
March 2008
Representational Power of Restricted Boltzmann Machines and Deep Belief Networks
Nicolas Le Roux, Yoshua Bengio
Neural Computation | January 2008
Continuous Neural Networks
Nicolas Le Roux, Yoshua Bengio
AISTAT2007 | January 2007
Convex Neural Networks
Yoshua Bengio, Nicolas Le Roux, Pascal Vincent, Olivier Delalleau, Patrice Marcotte
Advances in Neural Information Processing Systems 18 | Publié par MIT Press | 2006 | Advances in Neural Information Processing Systems 18 edition
-
Learning the 2-D Topology of Images
Nicolas Le Roux, Yoshua Bengio, Pascal Lamblin, Marc Joliveau, Balázs Kégl
NIPS2007 | January 2008
-
Spectral Dimensionality Reduction
Yoshua Bengio, Olivier Delalleau, Nicolas Le Roux, Jean-François Paiement, Pascal Vincent, Marie Ouimet
Feature Extraction, Foundations and Applications, Spectral Dimensionality Reduction | Publié par Springer | 2006
The Curse of Highly Variable Functions for Local Kernel Machines
Yoshua Bengio, Olivier Delalleau, Nicolas Le Roux
Advances in Neural Information Processing Systems 18 | January 2006
Learning eigenfunctions links spectral embedding and kernel PCA
Yoshua Bengio, Olivier Delalleau, Nicolas Le Roux, Jean-François Paiement, Pascal Vincent, Marie Ouimet
Neural Computation | January 2004, Vol 16: pp. 2197-2219
Spectral Clustering and Kernel PCA are Learning Eigenfunctions
Yoshua Bengio, Pascal Vincent, Jean-François Paiement, Olivier Delalleau, Marie Ouimet, Nicolas Le Roux
1239 | January 2003
-
Large-Scale Algorithms
Olivier Delalleau, Yoshua Bengio, Nicolas Le Roux
Semi-Supervised Learning | Publié par MIT Press | 2006 | Semi-Supervised Learning edition
Label Propagation and Quadratic Criterion
Yoshua Bengio, Olivier Delalleau, Nicolas Le Roux
Semi-Supervised Learning | Publié par MIT Press | 2006 | Semi-Supervised Learning edition
The Curse of Dimensionality for Local Kernel Machines
Yoshua Bengio, Olivier Delalleau, Nicolas Le Roux
TR-1258 | March 2005
-
Efficient Non-Parametric Function Induction in Semi-Supervised Learning
Olivier Delalleau, Yoshua Bengio, Nicolas Le Roux
Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics | January 2005
Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics
Publication Type
-
Language-guided Skill Learning with Temporal Variational Inference
Haotian Fu, Pratyusha Sharma, Elias Stengel-Eskin, George Konidaris, Nicolas Le Roux, Marc-Alexandre Côté, Xingdi Yuan
ICML 2024 | July 2024
Towards Modular LLMs by Building and Reusing a Library of LoRAs
O. Ostapenko, Zhan Su, E. Ponti, Laurent Charlin, Nicolas Le Roux, Matheus Pereira, Lucas Caccia, Alessandro Sordoni
ICML 2024 | May 2024
Multi-Head Adapter Routing for Cross-Task Generalization
Lucas Caccia, Edoardo Ponti, Zhan Su, Matheus Pereira, Nicolas Le Roux, Alessandro Sordoni
NeurIPS 2023 | October 2023
Joint Prompt Optimization of Stacked LLMs using Variational Inference
Alessandro Sordoni, Xingdi Yuan, Marc-Alexandre Côté, Matheus Pereira, Adam Trischler, Ziang Xiao, Arian Hosseini, Friederike Niedtner, Nicolas Le Roux
NeurIPS 2023 | October 2023
On the Convergence of Stochastic Extragradient for Bilinear Games using Restarted Iteration Averaging
Chris Junchi Li, Yaodong Yu, Nicolas Loizou, Gauthier Gidel, Yi Ma, Nicolas Le Roux, Michael I. Jordan
2022 International Conference on Artificial Intelligence and Statistics | March 2022
A general class of surrogate functions for stable and efficient reinforcement learning
Sharan Vaswani, Olivier Bachem, Simone Totaro, Robert Müller, Shivam Garg, Matthieu Geist, Marlos C. Machado, Pablo Samuel Castro, Nicolas Le Roux
2022 International Conference on Artificial Intelligence and Statistics | March 2022
Weakly Supervised Learning of Foreground-Background Segmentation using Masked RBMs
Nicolas Heess, Nicolas Le Roux, John Winn
International Conference on Artificial Neural Networks | January 2011
International Conference on Artificial Neural Networks
Topmoumoute online natural gradient algorithm
Nicolas Le Roux, Pierre-Antoine Manzagol, Yoshua Bengio
NIPS2007 | January 2008
Learning the 2-D Topology of Images
Nicolas Le Roux, Yoshua Bengio, Pascal Lamblin, Marc Joliveau, Balázs Kégl
NIPS2007 | January 2008
Continuous Neural Networks
Nicolas Le Roux, Yoshua Bengio
AISTAT2007 | January 2007
The Curse of Highly Variable Functions for Local Kernel Machines
Yoshua Bengio, Olivier Delalleau, Nicolas Le Roux
Advances in Neural Information Processing Systems 18 | January 2006
Efficient Non-Parametric Function Induction in Semi-Supervised Learning
Olivier Delalleau, Yoshua Bengio, Nicolas Le Roux
Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics | January 2005
Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics
-
Learning a Generative Model of Images by Factoring Appearance and Shape
Nicolas Le Roux, Nicolas Heess, Jamie Shotton, John Winn
Neural Computation | March 2011, Vol 23: pp. 593-650
Representational Power of Restricted Boltzmann Machines and Deep Belief Networks
Nicolas Le Roux, Yoshua Bengio
Neural Computation | January 2008
Learning eigenfunctions links spectral embedding and kernel PCA
Yoshua Bengio, Olivier Delalleau, Nicolas Le Roux, Jean-François Paiement, Pascal Vincent, Marie Ouimet
Neural Computation | January 2004, Vol 16: pp. 2197-2219
-
Avancées théoriques sur la représentation et l’optimisation des réseaux de neurones
Nicolas Le Roux, Le Roux, Nicolas
March 2008
March 2008
-
Spectral Dimensionality Reduction
Yoshua Bengio, Olivier Delalleau, Nicolas Le Roux, Jean-François Paiement, Pascal Vincent, Marie Ouimet
Feature Extraction, Foundations and Applications, Spectral Dimensionality Reduction | Publié par Springer | 2006
Convex Neural Networks
Yoshua Bengio, Nicolas Le Roux, Pascal Vincent, Olivier Delalleau, Patrice Marcotte
Advances in Neural Information Processing Systems 18 | Publié par MIT Press | 2006 | Advances in Neural Information Processing Systems 18 edition
Large-Scale Algorithms
Olivier Delalleau, Yoshua Bengio, Nicolas Le Roux
Semi-Supervised Learning | Publié par MIT Press | 2006 | Semi-Supervised Learning edition
Label Propagation and Quadratic Criterion
Yoshua Bengio, Olivier Delalleau, Nicolas Le Roux
Semi-Supervised Learning | Publié par MIT Press | 2006 | Semi-Supervised Learning edition
Out-of-Sample Extensions for LLE, Isomap, MDS, Eigenmaps, and Spectral Clustering
Yoshua Bengio, Jean-François Paiement, Pascal Vincent, Olivier Delalleau, Nicolas Le Roux, Marie Ouimet
Advances in Neural Information Processing Systems 16 | Publié par MIT Press | 2004 | Advances in Neural Information Processing Systems 16 edition
-
The Curse of Dimensionality for Local Kernel Machines
Yoshua Bengio, Olivier Delalleau, Nicolas Le Roux
TR-1258 | March 2005
Spectral Clustering and Kernel PCA are Learning Eigenfunctions
Yoshua Bengio, Pascal Vincent, Jean-François Paiement, Olivier Delalleau, Marie Ouimet, Nicolas Le Roux
1239 | January 2003