Yannis Flet-Berliac

According to our database, Yannis Flet-Berliac authored at least 17 papers between 2017 and 2024.

Collaborative distances:

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

2024

Averaging log-likelihoods in direct alignment.

Nathan Grinsztajn, Yannis Flet-Berliac, Mohammad Gheshlaghi Azar, Florian Strub, Bill Wu, Eugene Choi, Chris Cremer, Arash Ahmadian, Yash Chandak, Olivier Pietquin, Matthieu Geist

CoRR, 2024

Contrastive Policy Gradient: Aligning LLMs on sequence-level scores in a supervised-friendly fashion.

Yannis Flet-Berliac, Nathan Grinsztajn, Florian Strub, Eugene Choi, Chris Cremer, Arash Ahmadian, Yash Chandak, Mohammad Gheshlaghi Azar, Olivier Pietquin, Matthieu Geist

CoRR, 2024

OPERA: Automatic Offline Policy Evaluation with Re-weighted Aggregates of Multiple Estimators.

Allen Nie, Yash Chandak, Christina J. Yuan, Anirudhan Badrinath, Yannis Flet-Berliac, Emma Brunskill

CoRR, 2024

2023

PASTA: Pretrained Action-State Transformer Agents.

Raphaël Boige, Yannis Flet-Berliac, Arthur Flajolet, Guillaume Richard, Thomas Pierrot

CoRR, 2023

Waypoint Transformer: Reinforcement Learning via Supervised Learning with Intermediate Targets.

Anirudhan Badrinath, Yannis Flet-Berliac, Allen Nie, Emma Brunskill

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Model-Based Offline Reinforcement Learning with Local Misspecification.

Kefan Dong, Yannis Flet-Berliac, Allen Nie, Emma Brunskill

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

SAAC: Safe Reinforcement Learning as an Adversarial Game of Actor-Critics.

Yannis Flet-Berliac, Debabrota Basu

CoRR, 2022

Offline policy optimization with eligible actions.

Yao Liu, Yannis Flet-Berliac, Emma Brunskill

Proceedings of the Uncertainty in Artificial Intelligence, 2022

Data-Efficient Pipeline for Offline Reinforcement Learning with Limited Data.

Allen Nie, Yannis Flet-Berliac, Deon R. Jordan, William Steenbergen, Emma Brunskill

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Sample-Efficient Deep Reinforcement Learning for Control, Exploration and Safety. (Apprentissage par renforcement profond éfficace pour le contrôle, l'exploration et la sûreté).

Yannis Flet-Berliac

PhD thesis, 2021

Learning Value Functions in Deep Policy Gradients using Residual Variance.

Yannis Flet-Berliac, Reda Ouhamma, Odalric-Ambrym Maillard, Philippe Preux

Proceedings of the 9th International Conference on Learning Representations, 2021

Adversarially Guided Actor-Critic.

Yannis Flet-Berliac, Johan Ferret, Olivier Pietquin, Philippe Preux, Matthieu Geist

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Is Standard Deviation the New Standard? Revisiting the Critic in Deep Policy Gradients.

Yannis Flet-Berliac, Reda Ouhamma, Odalric-Ambrym Maillard, Philippe Preux

CoRR, 2020

Only Relevant Information Matters: Filtering Out Noisy Samples To Boost RL.

Yannis Flet-Berliac, Philippe Preux

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

2019

High-Dimensional Control Using Generalized Auxiliary Tasks.

Yannis Flet-Berliac, Philippe Preux

CoRR, 2019

Samples are not all useful: Denoising policy gradient updates using variance.

Yannis Flet-Berliac, Philippe Preux

CoRR, 2019

2017

Hearables in Hearing Care: Discovering Usage Patterns Through IoT Devices.

Benjamin Johansen, Yannis Paul Raymond Flet-Berliac, Maciej Jan Korzepa, Per Sandholm, Niels Henrik Pontoppidan, Michael Kai Petersen, Jakob Eg Larsen

Proceedings of the Universal Access in Human-Computer Interaction. Human and Technological Environments, 2017