Publications

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Model-based Offline Reinforcement Learning with Local Misspecification.
37th AAAI Conference on Artificial Intelligence (AAAI), 2023.

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Data-Efficient Pipeline for Offline Reinforcement Learning with Limited Data.
36th Conference on Neural Information Processing Systems (NeurIPS), 2022.

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Offline Policy Optimization with Eligible Actions.
38th Conference on Uncertainty in Artificial Intelligence (UAI), 2022.

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SAAC: Safe Reinforcement Learning as an Adversarial Game of Actor-Critics.
5th Conference on Reinforcement Learning and Decision Making (RLDM), 2022.

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Sample-Efficient Deep Reinforcement Learning for Control, Exploration and Safety.
PhD Thesis, 2021.

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Adversarially Guided Actor-Critic.
9th International Conference on Learning Representations (ICLR), 2021.

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Learning Value Functions in Deep Policy Gradients using Residual Variance.
9th International Conference on Learning Representations (ICLR), 2021.

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Only Relevant Information Matters: Filtering Out Noisy Samples to Boost RL.
29th International Joint Conference on Artificial Intelligence (IJCAI), 2020.

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Temperature Decreases Spread Parameters of the New Covid-19 Case Dynamics.
Biology, 9(5), p.94, 2020.

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MERL: Multi-Head Reinforcement Learning.
33rd Conference on Neural Information Processing Systems (NeurIPS), Deep RL Workshop, 2019.

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High-Dimensional Control Using Generalized Auxiliary Tasks.
Research Report hal-02295705, 2019.

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The Promise of Hierarchical Reinforcement Learning.
The Gradient, 2019.

Article


Hearables in Hearing Care: Discovering Usage Patterns Through IoT Devices.
International Conference on Universal Access in Human-Computer Interaction, 2017.

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