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ORCIDYannis Flet-Berliac
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2020 – today
- 2023
[c8]Kefan Dong, Yannis Flet-Berliac, Allen Nie, Emma Brunskill:
Model-Based Offline Reinforcement Learning with Local Misspecification. AAAI 2023: 7423-7431- [c7]Anirudhan Badrinath, Yannis Flet-Berliac, Allen Nie, Emma Brunskill:
Waypoint Transformer: Reinforcement Learning via Supervised Learning with Intermediate Targets. NeurIPS 2023 - [i10]Kefan Dong, Yannis Flet-Berliac, Allen Nie, Emma Brunskill:
Model-based Offline Reinforcement Learning with Local Misspecification. CoRR abs/2301.11426 (2023) - [i9]Anirudhan Badrinath, Yannis Flet-Berliac, Allen Nie, Emma Brunskill:
Waypoint Transformer: Reinforcement Learning via Supervised Learning with Intermediate Targets. CoRR abs/2306.14069 (2023) - [i8]Raphaël Boige, Yannis Flet-Berliac, Arthur Flajolet, Guillaume Richard, Thomas Pierrot:
PASTA: Pretrained Action-State Transformer Agents. CoRR abs/2307.10936 (2023) - 2022
- [c6]Allen Nie, Yannis Flet-Berliac, Deon R. Jordan, William Steenbergen, Emma Brunskill:
Data-Efficient Pipeline for Offline Reinforcement Learning with Limited Data. NeurIPS 2022 - [c5]Yao Liu, Yannis Flet-Berliac, Emma Brunskill:
Offline policy optimization with eligible actions. UAI 2022: 1253-1263 - [i7]Yannis Flet-Berliac, Debabrota Basu:
SAAC: Safe Reinforcement Learning as an Adversarial Game of Actor-Critics. CoRR abs/2204.09424 (2022) - [i6]Yao Liu, Yannis Flet-Berliac, Emma Brunskill:
Offline Policy Optimization with Eligible Actions. CoRR abs/2207.00632 (2022) - [i5]Allen Nie, Yannis Flet-Berliac, Deon R. Jordan, William Steenbergen, Emma Brunskill:
Data-Efficient Pipeline for Offline Reinforcement Learning with Limited Data. CoRR abs/2210.08642 (2022) - 2021
- [b1]Yannis Flet-Berliac:
Sample-Efficient Deep Reinforcement Learning for Control, Exploration and Safety. (Apprentissage par renforcement profond éfficace pour le contrôle, l'exploration et la sûreté). University of Lille, France, 2021 - [c4]Yannis Flet-Berliac, Johan Ferret, Olivier Pietquin, Philippe Preux, Matthieu Geist:
Adversarially Guided Actor-Critic. ICLR 2021 - [c3]Yannis Flet-Berliac, Reda Ouhamma, Odalric-Ambrym Maillard, Philippe Preux:
Learning Value Functions in Deep Policy Gradients using Residual Variance. ICLR 2021 - [i4]Yannis Flet-Berliac, Johan Ferret, Olivier Pietquin, Philippe Preux, Matthieu Geist:
Adversarially Guided Actor-Critic. CoRR abs/2102.04376 (2021) - 2020
- [c2]Yannis Flet-Berliac, Philippe Preux:
Only Relevant Information Matters: Filtering Out Noisy Samples To Boost RL. IJCAI 2020: 2711-2717 - [i3]Yannis Flet-Berliac, Reda Ouhamma, Odalric-Ambrym Maillard, Philippe Preux:
Is Standard Deviation the New Standard? Revisiting the Critic in Deep Policy Gradients. CoRR abs/2010.04440 (2020)
2010 – 2019
- 2019
- [i2]Yannis Flet-Berliac, Philippe Preux:
Samples are not all useful: Denoising policy gradient updates using variance. CoRR abs/1904.04025 (2019) - [i1]Yannis Flet-Berliac, Philippe Preux:
High-Dimensional Control Using Generalized Auxiliary Tasks. CoRR abs/1909.11939 (2019) - 2017
- [c1]Benjamin Johansen, Yannis Paul Raymond Flet-Berliac, Maciej Jan Korzepa, Per Sandholm, Niels Henrik Pontoppidan
, Michael Kai Petersen, Jakob Eg Larsen:
Hearables in Hearing Care: Discovering Usage Patterns Through IoT Devices. HCI (9) 2017: 39-49
Coauthor Index
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