Search Results - Bernardo Ávila Pires

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  1. 1
    Pseudo-MDPs and factored linear action models

    Pseudo-MDPs and factored linear action models by Hengshuai Yao, Szepesvari, Csaba, Pires, Bernardo Avila, Xinhua Zhang

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  2. 2
    Off-policy Distributional Q(\(\lambda\)): Distributional RL without Importance Sampling

    Off-policy Distributional Q(\(\lambda\)): Distributional RL without Importance Sampling by Tang, Yunhao, Rowland, Mark, Munos, Rémi, Bernardo Ávila Pires, Dabney, Will

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  3. 3
    DoMo-AC: Doubly Multi-step Off-policy Actor-Critic Algorithm

    DoMo-AC: Doubly Multi-step Off-policy Actor-Critic Algorithm by Tang, Yunhao, Kozuno, Tadashi, Rowland, Mark, Harutyunyan, Anna, Munos, Rémi, Bernardo Ávila Pires, Valko, Michal

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  4. 4
    Understanding the performance gap between online and offline alignment algorithms

    Understanding the performance gap between online and offline alignment algorithms by Tang, Yunhao, Guo, Daniel Zhaohan, Zheng, Zeyu, Calandriello, Daniele, Cao, Yuan, Tarassov, Eugene, Munos, Rémi, Bernardo Ávila Pires, Valko, Michal, Cheng, Yong, Dabney, Will

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  5. 5
    The Nature of Temporal Difference Errors in Multi-step Distributional Reinforcement Learning

    The Nature of Temporal Difference Errors in Multi-step Distributional Reinforcement Learning by Tang, Yunhao, Rowland, Mark, Munos, Rémi, Bernardo Ávila Pires, Dabney, Will, Bellemare, Marc G

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  6. 6
    Generalized Preference Optimization: A Unified Approach to Offline Alignment

    Generalized Preference Optimization: A Unified Approach to Offline Alignment by Tang, Yunhao, Guo, Zhaohan Daniel, Zheng, Zeyu, Calandriello, Daniele, Munos, Rémi, Rowland, Mark, Pierre Harvey Richemond, Valko, Michal, Bernardo Ávila Pires, Piot, Bilal

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  7. 7
    Multiclass Classification Calibration Functions

    Multiclass Classification Calibration Functions by Bernardo Ávila Pires, Szepesvári, Csaba

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  8. 8
    Policy Error Bounds for Model-Based Reinforcement Learning with Factored Linear Models

    Policy Error Bounds for Model-Based Reinforcement Learning with Factored Linear Models by Bernardo Ávila Pires, Szepesvári, Csaba

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  9. 9
    Understanding Self-Predictive Learning for Reinforcement Learning

    Understanding Self-Predictive Learning for Reinforcement Learning by Tang, Yunhao, Guo, Zhaohan Daniel, Pierre Harvey Richemond, Bernardo Ávila Pires, Chandak, Yash, Munos, Rémi, Rowland, Mark, Azar, Mohammad Gheshlaghi, Charline Le Lan, Lyle, Clare, György, András, Thakoor, Shantanu, Dabney, Will, Piot, Bilal, Calandriello, Daniele, Valko, Michal

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  10. 10
    Understanding plasticity in neural networks

    Understanding plasticity in neural networks by Lyle, Clare, Zheng, Zeyu, Nikishin, Evgenii, Bernardo Avila Pires, Pascanu, Razvan, Dabney, Will

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  11. 11
    Hierarchical Reinforcement Learning in Complex 3D Environments

    Hierarchical Reinforcement Learning in Complex 3D Environments by Bernardo Avila Pires, Behbahani, Feryal, Soyer, Hubert, Nikiforou, Kyriacos, Keck, Thomas, Singh, Satinder

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  12. 12
    A Unifying Framework for Action-Conditional Self-Predictive Reinforcement Learning

    A Unifying Framework for Action-Conditional Self-Predictive Reinforcement Learning by Khetarpal, Khimya, Guo, Zhaohan Daniel, Bernardo Avila Pires, Tang, Yunhao, Lyle, Clare, Rowland, Mark, Heess, Nicolas, Borsa, Diana, Guez, Arthur, Dabney, Will

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  13. 13
    Human Alignment of Large Language Models through Online Preference Optimisation

    Human Alignment of Large Language Models through Online Preference Optimisation by Calandriello, Daniele, Guo, Daniel, Munos, Remi, Rowland, Mark, Tang, Yunhao, Bernardo Avila Pires, Pierre Harvey Richemond, Charline Le Lan, Valko, Michal, Liu, Tianqi, Joshi, Rishabh, Zheng, Zeyu, Piot, Bilal

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  14. 14
    Neural Recursive Belief States in Multi-Agent Reinforcement Learning

    Neural Recursive Belief States in Multi-Agent Reinforcement Learning by Moreno, Pol, Hughes, Edward, McKee, Kevin R, Bernardo Avila Pires, Weber, Théophane

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  15. 15
    BYOL-Explore: Exploration by Bootstrapped Prediction

    BYOL-Explore: Exploration by Bootstrapped Prediction by Guo, Zhaohan Daniel, Thakoor, Shantanu, Pîslar, Miruna, Bernardo Avila Pires, Altché, Florent, Tallec, Corentin, Saade, Alaa, Calandriello, Daniele, Jean-Bastien Grill, Tang, Yunhao, Valko, Michal, Munos, Rémi, Azar, Mohammad Gheshlaghi, Piot, Bilal

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  16. 16
    Bootstrap Latent-Predictive Representations for Multitask Reinforcement Learning

    Bootstrap Latent-Predictive Representations for Multitask Reinforcement Learning by Guo, Daniel, Bernardo Avila Pires, Piot, Bilal, Jean-bastien Grill, Altché, Florent, Munos, Rémi, Azar, Mohammad Gheshlaghi

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  17. 17
    World Discovery Models

    World Discovery Models by Azar, Mohammad Gheshlaghi, Piot, Bilal, Bernardo Avila Pires, Jean-Bastian Grill, Altché, Florent, Munos, Rémi

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  18. 18
    Geometric Entropic Exploration

    Geometric Entropic Exploration by Guo, Zhaohan Daniel, Azar, Mohammad Gheshlaghi, Saade, Alaa, Thakoor, Shantanu, Piot, Bilal, Bernardo Avila Pires, Valko, Michal, Mesnard, Thomas, Lattimore, Tor, Munos, Rémi

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  19. 19
    Mine Your Own vieW: Self-Supervised Learning Through Across-Sample Prediction

    Mine Your Own vieW: Self-Supervised Learning Through Across-Sample Prediction by Azabou, Mehdi, Azar, Mohammad Gheshlaghi, Liu, Ran, Chi-Heng, Lin, Johnson, Erik C, Bhaskaran-Nair, Kiran, Dabagia, Max, Avila-Pires, Bernardo, Kitchell, Lindsey, Hengen, Keith B, Gray-Roncal, William, Valko, Michal, Dyer, Eva L

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  20. 20
    Statistical Linear Estimation with Penalized Estimators: an Application to Reinforcement Learning

    Statistical Linear Estimation with Penalized Estimators: an Application to Reinforcement Learning by Bernardo Avila Pires, Szepesvari, Csaba

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