Edouard Leurent

According to our database, Edouard Leurent authored at least 20 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of four.

2024

Conditioned Language Policy: A General Framework for Steerable Multi-Objective Finetuning.

Kaiwen Wang, Rahul Kidambi, Ryan Sullivan, Alekh Agarwal, Christoph Dann, Andrea Michi, Marco Gelmi, Yunxuan Li, Raghav Gupta, Avinava Dubey, Alexandre Ramé, Johan Ferret, Geoffrey Cideron, Le Hou, Hongkun Yu, Amr Ahmed, Aranyak Mehta, Léonard Hussenot, Olivier Bachem, Edouard Leurent

CoRR, 2024

Conditional Language Policy: A General Framework For Steerable Multi-Objective Finetuning.

Kaiwen Wang, Rahul Kidambi, Ryan Sullivan, Alekh Agarwal, Christoph Dann, Andrea Michi, Marco Gelmi, Yunxuan Li, Raghav Gupta, Kumar Dubey, Alexandre Ramé, Johan Ferret, Geoffrey Cideron, Le Hou, Hongkun Yu, Amr Ahmed, Aranyak Mehta, Léonard Hussenot, Olivier Bachem, Edouard Leurent

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

2023

Faster sorting algorithms discovered using deep reinforcement learning.

Daniel J. Mankowitz, Andrea Michi, Anton Zhernov, Marco Gelmi, Marco Selvi, Cosmin Paduraru, Edouard Leurent, Shariq Iqbal, Jean-Baptiste Lespiau, Alex Ahern, Thomas Köppe, Kevin Millikin, Stephen Gaffney, Sophie Elster, Jackson Broshear, Chris Gamble, Kieran Milan, Robert Tung, Minjae Hwang, A. Taylan Cemgil, Mohammadamin Barekatain, Yujia Li, Amol Mandhane, Thomas Hubert, Julian Schrittwieser, Demis Hassabis, Pushmeet Kohli, Martin A. Riedmiller, Oriol Vinyals, David Silver

Nat., 2023

Diversifying AI: Towards Creative Chess with AlphaZero.

Tom Zahavy, Vivek Veeriah, Shaobo Hou, Kevin Waugh, Matthew Lai, Edouard Leurent, Nenad Tomasev, Lisa Schut, Demis Hassabis, Satinder Singh

CoRR, 2023

Optimizing Memory Mapping Using Deep Reinforcement Learning.

Pengming Wang, Mikita Sazanovich, Berkin Ilbeyi, Phitchaya Mangpo Phothilimthana, Manish Purohit, Han Yang Tay, Ngân Vu, Miaosen Wang, Cosmin Paduraru, Edouard Leurent, Anton Zhernov, Julian Schrittwieser, Thomas Hubert, Robert Tung, Paula Kurylowicz, Kieran Milan, Oriol Vinyals, Daniel J. Mankowitz

CoRR, 2023

2022

Automated Planning for Robotic Guidewire Navigation in the Coronary Arteries.

Pierre Schegg, Jérémie Dequidt, Eulalie Coevoet, Edouard Leurent, Rémi Sabatier, Philippe Preux, Christian Duriez

Proceedings of the 5th IEEE International Conference on Soft Robotics, 2022

2021

Fast active learning for pure exploration in reinforcement learning.

Pierre Ménard, Omar Darwiche Domingues, Anders Jonsson, Emilie Kaufmann, Edouard Leurent, Michal Valko

Proceedings of the 38th International Conference on Machine Learning, 2021

Adaptive Reward-Free Exploration.

Emilie Kaufmann, Pierre Ménard, Omar Darwiche Domingues, Anders Jonsson, Edouard Leurent, Michal Valko

Proceedings of the Algorithmic Learning Theory, 2021

2020

Safe and Efficient Reinforcement Learning for Behavioural Planning in Autonomous Driving. (Apprentissage par renforcement sûr et efficace pour la planification comportementale en conduite autonome).

Edouard Leurent

PhD thesis, 2020

Robust Estimation, Prediction and Control with Linear Dynamics and Generic Costs.

Edouard Leurent, Denis V. Efimov, Odalric-Ambrym Maillard

CoRR, 2020

Robust-Adaptive Control of Linear Systems: beyond Quadratic Costs.

Edouard Leurent, Odalric-Ambrym Maillard, Denis V. Efimov

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Planning in Markov Decision Processes with Gap-Dependent Sample Complexity.

Anders Jonsson, Emilie Kaufmann, Pierre Ménard, Omar Darwiche Domingues, Edouard Leurent, Michal Valko

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Robust-Adaptive Interval Predictive Control for Linear Uncertain Systems.

Edouard Leurent, Denis V. Efimov, Odalric-Ambrym Maillard

Proceedings of the 59th IEEE Conference on Decision and Control, 2020

Monte-Carlo Graph Search: the Value of Merging Similar States.

Edouard Leurent, Odalric-Ambrym Maillard

Proceedings of The 12th Asian Conference on Machine Learning, 2020

2019

Social Attention for Autonomous Decision-Making in Dense Traffic.

Edouard Leurent, Jean Mercat

CoRR, 2019

Scaling up budgeted reinforcement learning.

Nicolas Carrara, Edouard Leurent, Romain Laroche, Tanguy Urvoy, Odalric-Ambrym Maillard, Olivier Pietquin

CoRR, 2019

Approximate Robust Control of Uncertain Dynamical Systems.

Edouard Leurent, Yann Blanco, Denis V. Efimov, Odalric-Ambrym Maillard

CoRR, 2019

Practical Open-Loop Optimistic Planning.

Edouard Leurent, Odalric-Ambrym Maillard

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

Budgeted Reinforcement Learning in Continuous State Space.

Nicolas Carrara, Edouard Leurent, Romain Laroche, Tanguy Urvoy, Odalric-Ambrym Maillard, Olivier Pietquin

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Interval Prediction for Continuous-Time Systems with Parametric Uncertainties.

Edouard Leurent, Denis V. Efimov, Tarek Raïssi, Wilfrid Perruquetti

Proceedings of the 58th IEEE Conference on Decision and Control, 2019