Alberto Maria Metelli

Venues

Frequent coauthors

Papers

1. Achieving $\widetilde{\mathcal{O}}(\sqrt{T})$ Regret in Average-Reward POMDPs with Known Observation Models
   AISTATS 2025 ·

   Alessio Russo

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2. Convergence Analysis of Policy Gradient Methods with Dynamic Stochasticity
   ICML 2025 ·

   Alessandro Montenegro

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3. Efficient Exploitation of Hierarchical Structure in Sparse Reward Reinforcement Learning
   AISTATS 2025 ·

   Gianluca Drappo

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4. Learning Utilities from Demonstrations in Markov Decision Processes
   ICML 2025 ·

   Filippo Lazzati

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5. Open Problem: Regret Minimization in Heavy-Tailed Bandits with Unknown Distributional Parameters
   COLT 2025 ·

   Gianmarco Genalti

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6. Position: Constants are Critical in Regret Bounds for Reinforcement Learning
   ICML 2025 ·

   Simone Drago

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7. Sleeping Reinforcement Learning
   ICML 2025 ·

   Simone Drago

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8. Spectral Learning for Infinite-Horizon Average-Reward POMDPs
   NeurIPS 2025 ·

   Alessio Russo

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9. Tightening Regret Lower and Upper Bounds in Restless Rising Bandits
   NeurIPS 2025 ·

   Cristiano Migali

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10. Towards Theoretical Understanding of Sequential Decision Making with Preference Feedback
    ICML 2025 ·

    Simone Drago

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11. (ε, u)-Adaptive Regret Minimization in Heavy-Tailed Bandits
    COLT 2024 ·

    Gianmarco Genalti

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12. Autoregressive Bandits
    AISTATS 2024 ·

    Francesco Bacchiocchi

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13. Best Arm Identification for Stochastic Rising Bandits
    ICML 2024 ·

    Marco Mussi

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14. Dissimilarity Bandits
    AISTATS 2024 ·

    Paolo Battellani

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15. Factored-Reward Bandits with Intermediate Observations
    ICML 2024 ·

    Marco Mussi

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16. Graph-Triggered Rising Bandits
    ICML 2024 ·

    Gianmarco Genalti

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17. How does Inverse RL Scale to Large State Spaces? A Provably Efficient Approach
    NeurIPS 2024 ·

    Filippo Lazzati

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18. Interpetable Target-Feature Aggregation for Multi-task Learning Based on Bias-Variance Analysis
    ECML-PKDD 2024 ·

    Paolo Bonetti

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19. Last-Iterate Global Convergence of Policy Gradients for Constrained Reinforcement Learning
    NeurIPS 2024 ·

    Alessandro Montenegro

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20. Learning Optimal Deterministic Policies with Stochastic Policy Gradients
    ICML 2024 ·

    Alessandro Montenegro

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21. Local Linearity: the Key for No-regret Reinforcement Learning in Continuous MDPs
    NeurIPS 2024 ·

    Davide Maran

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22. No-Regret Reinforcement Learning in Smooth MDPs
    ICML 2024 ·

    Davide Maran

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23. Offline Inverse RL: New Solution Concepts and Provably Efficient Algorithms
    ICML 2024 ·

    Filippo Lazzati

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24. Online Learning with Off-Policy Feedback in Adversarial MDPs
    IJCAI 2024 ·

    Francesco Bacchiocchi

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25. Optimal Multi-Fidelity Best-Arm Identification
    NeurIPS 2024 ·

    Riccardo Poiani

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26. Parameterized Projected Bellman Operator
    AAAI 2024 ·

    Théo Vincent

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27. Projection by Convolution: Optimal Sample Complexity for Reinforcement Learning in Continuous-Space MDPs
    COLT 2024 ·

    Davide Maran

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28. Recent Advancements in Inverse Reinforcement Learning
    AAAI 2024 · Alberto Maria Metelli
29. Sub-optimal Experts mitigate Ambiguity in Inverse Reinforcement Learning
    NeurIPS 2024 ·

    Riccardo Poiani

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