Le Roux, Nicolas

38 publications

AISTATS 2025 Fast Convergence of SoftMax Policy Mirror Ascent Reza Asad, Reza Babanezhad Harikandeh, Issam H. Laradji, Nicolas Le Roux, Sharan Vaswani

NeurIPS 2025 Tapered Off-Policy REINFORCE - Stable and Efficient Reinforcement Learning for Large Language Models Nicolas Le Roux, Marc G Bellemare, Jonathan Lebensold, Arnaud Bergeron, Joshua Greaves, Alexandre Fréchette, Carolyne Pelletier, Eric Thibodeau-Laufer, Sándor Tóth, Sam Work

ICML 2025 VinePPO: Refining Credit Assignment in RL Training of LLMs Amirhossein Kazemnejad, Milad Aghajohari, Eva Portelance, Alessandro Sordoni, Siva Reddy, Aaron Courville, Nicolas Le Roux

NeurIPSW 2024 Fast Convergence of SoftMax Policy Mirror Ascent for Bandits & Tabular MDPs Reza Asad, Reza Babanezhad Harikandeh, Issam H. Laradji, Nicolas Le Roux, Sharan Vaswani

NeurIPSW 2024 How Learning Rates Shape Neural Network Focus: Insights from Example Ranking Ekaterina Lobacheva, Keller Jordan, Aristide Baratin, Nicolas Le Roux

NeurIPS 2024 Improving Context-Aware Preference Modeling for Language Models Silviu Pitis, Ziang Xiao, Nicolas Le Roux, Alessandro Sordoni

ICML 2024 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

ICLRW 2024 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 Towards Modular LLMs by Building and Reusing a Library of LoRAs Oleksiy Ostapenko, Zhan Su, Edoardo Ponti, Laurent Charlin, Nicolas Le Roux, Lucas Caccia, Alessandro Sordoni

NeurIPSW 2024 VinePPO: Accurate Credit Assignment in RL for LLM Mathematical Reasoning Amirhossein Kazemnejad, Milad Aghajohari, Eva Portelance, Alessandro Sordoni, Siva Reddy, Aaron Courville, Nicolas Le Roux

NeurIPSW 2023 A Case Study of Instruction Tuning with Mixture of Parameter-Efficient Experts Oleksiy Ostapenko, Lucas Caccia, Zhan Su, Nicolas Le Roux, Laurent Charlin, Alessandro Sordoni

NeurIPS 2023 Decision-Aware Actor-Critic with Function Approximation and Theoretical Guarantees Sharan Vaswani, Amirreza Kazemi, Reza Babanezhad Harikandeh, Nicolas Le Roux

NeurIPS 2023 Joint Prompt Optimization of Stacked LLMs Using Variational Inference Alessandro Sordoni, Eric Yuan, Marc-Alexandre Côté, Matheus Pereira, Adam Trischler, Ziang Xiao, Arian Hosseini, Friederike Niedtner, Nicolas Le Roux

NeurIPS 2023 Multi-Head Adapter Routing for Cross-Task Generalization Lucas Page-Caccia, Edoardo Maria Ponti, Zhan Su, Matheus Pereira, Nicolas Le Roux, Alessandro Sordoni

NeurIPSW 2023 Surrogate Minimization: An Optimization Algorithm for Training Large Neural Networks with Model Parallelism Reza Asad, Reza Babanezhad Harikandeh, Issam H. Laradji, Nicolas Le Roux, Sharan Vaswani

ICML 2023 Target-Based Surrogates for Stochastic Optimization Jonathan Wilder Lavington, Sharan Vaswani, Reza Babanezhad Harikandeh, Mark Schmidt, Nicolas Le Roux

AISTATS 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

AISTATS 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 Jordan

NeurIPSW 2022 Target-Based Surrogates for Stochastic Optimization Jonathan Wilder Lavington, Sharan Vaswani, Reza Babanezhad Harikandeh, Mark Schmidt, Nicolas Le Roux

ICLR 2021 Batch Reinforcement Learning Through Continuation Method Yijie Guo, Shengyu Feng, Nicolas Le Roux, Ed Chi, Honglak Lee, Minmin Chen

ICML 2021 Beyond Variance Reduction: Understanding the True Impact of Baselines on Policy Optimization Wesley Chung, Valentin Thomas, Marlos C. Machado, Nicolas Le Roux

ICCV 2021 Impact of Aliasing on Generalization in Deep Convolutional Networks Cristina Vasconcelos, Hugo Larochelle, Vincent Dumoulin, Rob Romijnders, Nicolas Le Roux, Ross Goroshin

NeurIPS 2020 An Operator View of Policy Gradient Methods Dibya Ghosh, Marlos C. Machado, Nicolas Le Roux

AISTATS 2020 On the Interplay Between Noise and Curvature and Its Effect on Optimization and Generalization Valentin Thomas, Fabian Pedregosa, Bart Merriënboer, Pierre-Antoine Manzagol, Yoshua Bengio, Nicolas Le Roux

ICLR 2020 The Geometry of Sign Gradient Descent Lukas Balles, Fabian Pedregosa, Nicolas Le Roux

NeurIPS 2019 A Geometric Perspective on Optimal Representations for Reinforcement Learning Marc Bellemare, Will Dabney, Robert Dadashi, Adrien Ali Taiga, Pablo Samuel Castro, Nicolas Le Roux, Dale Schuurmans, Tor Lattimore, Clare Lyle

AISTATS 2019 Distributional Reinforcement Learning with Linear Function Approximation Marc G. Bellemare, Nicolas Le Roux, Pablo Samuel Castro, Subhodeep Moitra

NeurIPS 2019 Reducing the Variance in Online Optimization by Transporting past Gradients Sébastien Arnold, Pierre-Antoine Manzagol, Reza Babanezhad Harikandeh, Ioannis Mitliagkas, Nicolas Le Roux

ICML 2019 The Value Function Polytope in Reinforcement Learning Robert Dadashi, Adrien Ali Taiga, Nicolas Le Roux, Dale Schuurmans, Marc G. Bellemare

ICML 2019 Understanding the Impact of Entropy on Policy Optimization Zafarali Ahmed, Nicolas Le Roux, Mohammad Norouzi, Dale Schuurmans

AISTATS 2018 Tracking the Gradients Using the Hessian: A New Look at Variance Reducing Stochastic Methods Robert M. Gower, Nicolas Le Roux, Francis R. Bach

ICLR 2017 Tighter Bounds Lead to Improved Classifiers Nicolas Le Roux

ICLR 2013 Local Component Analysis Nicolas Le Roux, Francis R. Bach

ICCV 2011 Ask the Locals: Multi-Way Local Pooling for Image Recognition Y-Lan Boureau, Nicolas Le Roux, Francis R. Bach, Jean Ponce, Yann LeCun

ICML 2010 A Fast Natural Newton Method Nicolas Le Roux, Andrew W. Fitzgibbon

AISTATS 2007 Continuous Neural Networks Nicolas Le Roux, Yoshua Bengio

AISTATS 2005 Efficient Non-Parametric Function Induction in Semi-Supervised Learning Olivier Delalleau, Yoshua Bengio, Nicolas Le Roux

NeCo 2004 Learning Eigenfunctions Links Spectral Embedding and Kernel PCA Yoshua Bengio, Olivier Delalleau, Nicolas Le Roux, Jean-François Paiement, Pascal Vincent, Marie Ouimet