Restelli, Marcello

132 publications

AISTATS 2025 Achieving $\widetilde\mathcal{O}(\sqrt{T})$ Regret in Average-Reward POMDPs with Known Observation Models Alessio Russo, Alberto Maria Metelli, Marcello Restelli

AISTATS 2025 Efficient Exploitation of Hierarchical Structure in Sparse Reward Reinforcement Learning Gianluca Drappo, Arnaud Robert, Marcello Restelli, Aldo A. Faisal, Alberto Maria Metelli, Ciara Pike-Burke

ICML 2025 Enhancing Diversity in Parallel Agents: A Maximum State Entropy Exploration Story Vincenzo De Paola, Riccardo Zamboni, Mirco Mutti, Marcello Restelli

MLJ 2025 Search or Split: Policy Gradient with Adaptive Policy Space Gianmarco Tedeschi, Matteo Papini, Alberto Maria Metelli, Marcello Restelli

NeurIPS 2025 Spectral Learning for Infinite-Horizon Average-Reward POMDPs Alessio Russo, Alberto Maria Metelli, Marcello Restelli

NeurIPS 2025 Towards Principled Unsupervised Multi-Agent Reinforcement Learning Riccardo Zamboni, Mirco Mutti, Marcello Restelli

NeurIPS 2024 A Retrospective on the Robot Air Hockey Challenge: Benchmarking Robust, Reliable, and Safe Learning Techniques for Real-World Robotics Puze Liu, Jonas Günster, Niklas Funk, Simon Gröger, Dong Chen, Haitham Bou-Ammar, Julius Jankowski, Ante Marić, Sylvain Calinon, Andrej Orsula, Miguel Olivares-Mendez, Hongyi Zhou, Rudolf Lioutikov, Gerhard Neumann, Amarildo Likmeta, Amirhossein Zhalehmehrabi, Thomas Bonenfant, Marcello Restelli, Davide Tateo, Ziyuan Liu, Jan Peters

AISTATS 2024 Autoregressive Bandits Francesco Bacchiocchi, Gianmarco Genalti, Davide Maran, Marco Mussi, Marcello Restelli, Nicola Gatti, Alberto Maria Metelli

NeurIPS 2024 Bandits with Ranking Feedback Davide Maran, Francesco Bacchiocchi, Francesco Emanuele Stradi, Matteo Castiglioni, Nicola Gatti, Marcello Restelli

ICML 2024 Best Arm Identification for Stochastic Rising Bandits Marco Mussi, Alessandro Montenegro, Francesco Trovò, Marcello Restelli, Alberto Maria Metelli

ICLR 2024 Exploiting Causal Graph Priors with Posterior Sampling for Reinforcement Learning Mirco Mutti, Riccardo De Santi, Marcello Restelli, Alexander Marx, Giorgia Ramponi

ICML 2024 Factored-Reward Bandits with Intermediate Observations Marco Mussi, Simone Drago, Marcello Restelli, Alberto Maria Metelli

ICML 2024 Graph-Triggered Rising Bandits Gianmarco Genalti, Marco Mussi, Nicola Gatti, Marcello Restelli, Matteo Castiglioni, Alberto Maria Metelli

ICML 2024 How to Explore with Belief: State Entropy Maximization in POMDPs Riccardo Zamboni, Duilio Cirino, Marcello Restelli, Mirco Mutti

JMLR 2024 Information Capacity Regret Bounds for Bandits with Mediator Feedback Khaled Eldowa, Nicolò Cesa-Bianchi, Alberto Maria Metelli, Marcello Restelli

ECML-PKDD 2024 Interpetable Target-Feature Aggregation for Multi-Task Learning Based on Bias-Variance Analysis Paolo Bonetti, Alberto Maria Metelli, Marcello Restelli

NeurIPS 2024 Local Linearity: The Key for No-Regret Reinforcement Learning in Continuous MDPs Davide Maran, Alberto Maria Metelli, Matteo Papini, Marcello Restelli

ICML 2024 No-Regret Reinforcement Learning in Smooth MDPs Davide Maran, Alberto Maria Metelli, Matteo Papini, Marcello Restelli

AAAI 2024 Online Markov Decision Processes Configuration with Continuous Decision Space Davide Maran, Pierriccardo Olivieri, Francesco Emanuele Stradi, Giuseppe Urso, Nicola Gatti, Marcello Restelli

NeurIPS 2024 Optimal Multi-Fidelity Best-Arm Identification Riccardo Poiani, Rémy Degenne, Emilie Kaufmann, Alberto Maria Metelli, Marcello Restelli

AAAI 2024 Parameterized Projected Bellman Operator Théo Vincent, Alberto Maria Metelli, Boris Belousov, Jan Peters, Marcello Restelli, Carlo D'Eramo

ICMLW 2024 Policy Gradient Methods with Adaptive Policy Spaces Gianmarco Tedeschi, Matteo Papini, Marcello Restelli

COLT 2024 Projection by Convolution: Optimal Sample Complexity for Reinforcement Learning in Continuous-Space MDPs Davide Maran, Alberto Maria Metelli, Matteo Papini, Marcello Restelli

MLJ 2024 Sample Complexity of Variance-Reduced Policy Gradient: Weaker Assumptions and Lower Bounds Gabor Paczolay, Matteo Papini, Alberto Maria Metelli, István Á. Harmati, Marcello Restelli

NeurIPS 2024 Sub-Optimal Experts Mitigate Ambiguity in Inverse Reinforcement Learning Riccardo Poiani, Gabriele Curti, Alberto Maria Metelli, Marcello Restelli

TMLR 2024 Switching Latent Bandits Alessio Russo, Alberto Maria Metelli, Marcello Restelli

ICMLW 2023 A Best Arm Identification Approach for Stochastic Rising Bandits Alessandro Montenegro, Marco Mussi, Francesco Trovò, Marcello Restelli, Alberto Maria Metelli

AISTATS 2023 A Tale of Sampling and Estimation in Discounted Reinforcement Learning Alberto Maria Metelli, Mirco Mutti, Marcello Restelli

TMLR 2023 An Option-Dependent Analysis of Regret Minimization Algorithms in Finite-Horizon Semi-MDP Gianluca Drappo, Alberto Maria Metelli, Marcello Restelli

JMLR 2023 Convex Reinforcement Learning in Finite Trials Mirco Mutti, Riccardo De Santi, Piersilvio De Bartolomeis, Marcello Restelli

NeurIPS 2023 Distributional Policy Evaluation: A Maximum Entropy Approach to Representation Learning Riccardo Zamboni, Alberto Maria Metelli, Marcello Restelli

AAAI 2023 Dynamic Pricing with Volume Discounts in Online Settings Marco Mussi, Gianmarco Genalti, Alessandro Nuara, Francesco Trovò, Marcello Restelli, Nicola Gatti

ICML 2023 Dynamical Linear Bandits Marco Mussi, Alberto Maria Metelli, Marcello Restelli

NeurIPSW 2023 Exploiting Causal Representations in Reinforcement Learning: A Posterior Sampling Approach Mirco Mutti, Riccardo De Santi, Marcello Restelli, Alexander Marx, Giorgia Ramponi

UAI 2023 On the Relation Between Policy Improvement and Off-Policy Minimum-Variance Policy Evaluation Alberto Maria Metelli, Samuele Meta, Marcello Restelli

ICMLW 2023 Parameterized Projected Bellman Operator Théo Vincent, Alberto Maria Metelli, Jan Peters, Marcello Restelli, Carlo D'Eramo

AAAI 2023 Provably Efficient Causal Model-Based Reinforcement Learning for Systematic Generalization Mirco Mutti, Riccardo De Santi, Emanuele Rossi, Juan Felipe Calderón, Michael M. Bronstein, Marcello Restelli

NeurIPSW 2023 Pure Exploration Under Mediators’ Feedback Riccardo Poiani, Alberto Maria Metelli, Marcello Restelli

AAAI 2023 Simultaneously Updating All Persistence Values in Reinforcement Learning Luca Sabbioni, Luca Al Daire, Lorenzo Bisi, Alberto Maria Metelli, Marcello Restelli

ECML-PKDD 2023 Stepsize Learning for Policy Gradient Methods in Contextual Markov Decision Processes Luca Sabbioni, Francesco Corda, Marcello Restelli

AAAI 2023 Tight Performance Guarantees of Imitator Policies with Continuous Actions Davide Maran, Alberto Maria Metelli, Marcello Restelli

ICML 2023 Towards Theoretical Understanding of Inverse Reinforcement Learning Alberto Maria Metelli, Filippo Lazzati, Marcello Restelli

NeurIPS 2023 Truncating Trajectories in Monte Carlo Policy Evaluation: An Adaptive Approach Riccardo Poiani, Nicole Nobili, Alberto Maria Metelli, Marcello Restelli

ICML 2023 Truncating Trajectories in Monte Carlo Reinforcement Learning Riccardo Poiani, Alberto Maria Metelli, Marcello Restelli

AAAI 2023 Wasserstein Actor-Critic: Directed Exploration via Optimism for Continuous-Actions Control Amarildo Likmeta, Matteo Sacco, Alberto Maria Metelli, Marcello Restelli

AISTATS 2022 Finite Sample Analysis of Mean-Volatility Actor-Critic for Risk-Averse Reinforcement Learning Khaled Eldowa, Lorenzo Bisi, Marcello Restelli

AISTATS 2022 Reward-Free Policy Space Compression for Reinforcement Learning Mirco Mutti, Stefano Del Col, Marcello Restelli

ICML 2022 Balancing Sample Efficiency and Suboptimality in Inverse Reinforcement Learning Angelo Damiani, Giorgio Manganini, Alberto Maria Metelli, Marcello Restelli

NeurIPS 2022 Challenging Common Assumptions in Convex Reinforcement Learning Mirco Mutti, Riccardo De Santi, Piersilvio De Bartolomeis, Marcello Restelli

ICML 2022 Delayed Reinforcement Learning by Imitation Pierre Liotet, Davide Maran, Lorenzo Bisi, Marcello Restelli

ICMLW 2022 Directed Exploration via Uncertainty-Aware Critics Amarildo Likmeta, Matteo Sacco, Alberto Maria Metelli, Marcello Restelli

ICLR 2022 Goal-Directed Planning via Hindsight Experience Replay Lorenzo Moro, Amarildo Likmeta, Enrico Prati, Marcello Restelli

ICMLW 2022 Invariance Discovery for Systematic Generalization in Reinforcement Learning Mirco Mutti, Riccardo De Santi, Emanuele Rossi, Juan Felipe Calderon, Michael M. Bronstein, Marcello Restelli

UAI 2022 Learning in Markov Games: Can We Exploit a General-Sum Opponent? Giorgia Ramponi, Marcello Restelli

AAAI 2022 Lifelong Hyper-Policy Optimization with Multiple Importance Sampling Regularization Pierre Liotet, Francesco Vidaich, Alberto Maria Metelli, Marcello Restelli

IJCAI 2022 Multi-Armed Bandit Problem with Temporally-Partitioned Rewards: When Partial Feedback Counts Giulia Romano, Andrea Agostini, Francesco Trovò, Nicola Gatti, Marcello Restelli

NeurIPS 2022 Multi-Fidelity Best-Arm Identification Riccardo Poiani, Alberto Maria Metelli, Marcello Restelli

ICMLW 2022 Non-Markovian Policies for Unsupervised Reinforcement Learning in Multiple Environments Pietro Maldini, Mirco Mutti, Riccardo De Santi, Marcello Restelli

ICMLW 2022 Non-Markovian Policies for Unsupervised Reinforcement Learning in Multiple Environments Pietro Maldini, Mirco Mutti, Riccardo De Santi, Marcello Restelli

NeurIPS 2022 Off-Policy Evaluation with Deficient Support Using Side Information Nicolò Felicioni, Maurizio Ferrari Dacrema, Marcello Restelli, Paolo Cremonesi

MLJ 2022 Policy Space Identification in Configurable Environments Alberto Maria Metelli, Guglielmo Manneschi, Marcello Restelli

NeurIPSW 2022 Provably Efficient Causal Model-Based Reinforcement Learning for Environment-Agnostic Generalization Mirco Mutti, Riccardo De Santi, Emanuele Rossi, Juan Felipe Calderon, Michael M. Bronstein, Marcello Restelli

MLJ 2022 Smoothing Policies and Safe Policy Gradients Matteo Papini, Matteo Pirotta, Marcello Restelli

ICML 2022 Stochastic Rising Bandits Alberto Maria Metelli, Francesco Trovò, Matteo Pirola, Marcello Restelli

ICML 2022 The Importance of Non-Markovianity in Maximum State Entropy Exploration Mirco Mutti, Riccardo De Santi, Marcello Restelli

AAAI 2022 Unsupervised Reinforcement Learning in Multiple Environments Mirco Mutti, Mattia Mancassola, Marcello Restelli

ECML-PKDD 2021 Conservative Online Convex Optimization Martino Bernasconi de Luca, Edoardo Vittori, Francesco Trovò, Marcello Restelli

MLJ 2021 Dealing with Multiple Experts and Non-Stationarity in Inverse Reinforcement Learning: An Application to Real-Life Problems Amarildo Likmeta, Alberto Maria Metelli, Giorgia Ramponi, Andrea Tirinzoni, Matteo Giuliani, Marcello Restelli

ECML-PKDD 2021 Exploiting History Data for Nonstationary Multi-Armed Bandit Gerlando Re, Fabio Chiusano, Francesco Trovò, Diego Carrera, Giacomo Boracchi, Marcello Restelli

JMLR 2021 Gaussian Approximation for Bias Reduction in Q-Learning Carlo D'Eramo, Andrea Cini, Alessandro Nuara, Matteo Pirotta, Cesare Alippi, Jan Peters, Marcello Restelli

NeurIPS 2021 Learning in Non-Cooperative Configurable Markov Decision Processes Giorgia Ramponi, Alberto Maria Metelli, Alessandro Concetti, Marcello Restelli

ICMLW 2021 Learning to Explore Multiple Environments Without Rewards Mirco Mutti, Mattia Mancassola, Marcello Restelli

ICML 2021 Leveraging Good Representations in Linear Contextual Bandits Matteo Papini, Andrea Tirinzoni, Marcello Restelli, Alessandro Lazaric, Matteo Pirotta

ICMLW 2021 Meta Learning the Step Size in Policy Gradient Methods Luca Sabbioni, Francesco Corda, Marcello Restelli

IJCAI 2021 Meta-Reinforcement Learning by Tracking Task Non-Stationarity Riccardo Poiani, Andrea Tirinzoni, Marcello Restelli

MLOSS 2021 MushroomRL: Simplifying Reinforcement Learning Research Carlo D'Eramo, Davide Tateo, Andrea Bonarini, Marcello Restelli, Jan Peters

AAAI 2021 Newton Optimization on Helmholtz Decomposition for Continuous Games Giorgia Ramponi, Marcello Restelli

AAAI 2021 Policy Optimization as Online Learning with Mediator Feedback Alberto Maria Metelli, Matteo Papini, Pierluca D'Oro, Marcello Restelli

NeurIPSW 2021 Policy Optimization via Optimal Policy Evaluation Alberto Maria Metelli, Samuele Meta, Marcello Restelli

ICML 2021 Provably Efficient Learning of Transferable Rewards Alberto Maria Metelli, Giorgia Ramponi, Alessandro Concetti, Marcello Restelli

NeurIPS 2021 Reinforcement Learning in Linear MDPs: Constant Regret and Representation Selection Matteo Papini, Andrea Tirinzoni, Aldo Pacchiano, Marcello Restelli, Alessandro Lazaric, Matteo Pirotta

ICMLW 2021 Reward-Free Policy Space Compression for Reinforcement Learning Mirco Mutti, Stefano Del Col, Marcello Restelli

JMLR 2021 Safe Policy Iteration: A Monotonically Improving Approximate Policy Iteration Approach Alberto Maria Metelli, Matteo Pirotta, Daniele Calandriello, Marcello Restelli

NeurIPS 2021 Subgaussian and Differentiable Importance Sampling for Off-Policy Evaluation and Learning Alberto Maria Metelli, Alessio Russo, Marcello Restelli

AAAI 2021 Task-Agnostic Exploration via Policy Gradient of a Non-Parametric State Entropy Estimate Mirco Mutti, Lorenzo Pratissoli, Marcello Restelli

ICMLW 2021 The Importance of Non-Markovianity in Maximum State Entropy Exploration Mirco Mutti, Riccardo De Santi, Marcello Restelli

UAI 2021 Time-Variant Variational Transfer for Value Functions Giuseppe Canonaco, Andrea Soprani, Matteo Giuliani, Andrea Castelletti, Manuel Roveri, Marcello Restelli

AISTATS 2020 A Novel Confidence-Based Algorithm for Structured Bandits Andrea Tirinzoni, Alessandro Lazaric, Marcello Restelli

ICMLW 2020 A Policy Gradient Method for Task-Agnostic Exploration Mirco Mutti, Lorenzo Pratissoli, Marcello Restelli

NeurIPS 2020 An Asymptotically Optimal Primal-Dual Incremental Algorithm for Contextual Linear Bandits Andrea Tirinzoni, Matteo Pirotta, Marcello Restelli, Alessandro Lazaric

AAAI 2020 An Intrinsically-Motivated Approach for Learning Highly Exploring and Fast Mixing Policies Mirco Mutti, Marcello Restelli

AISTATS 2020 Balancing Learning Speed and Stability in Policy Gradient via Adaptive Exploration Matteo Papini, Andrea Battistello, Marcello Restelli

ICML 2020 Control Frequency Adaptation via Action Persistence in Batch Reinforcement Learning Alberto Maria Metelli, Flavio Mazzolini, Lorenzo Bisi, Luca Sabbioni, Marcello Restelli

AAAI 2020 Gradient-Aware Model-Based Policy Search Pierluca D'Oro, Alberto Maria Metelli, Andrea Tirinzoni, Matteo Papini, Marcello Restelli

JMLR 2020 Importance Sampling Techniques for Policy Optimization Alberto Maria Metelli, Matteo Papini, Nico Montali, Marcello Restelli

NeurIPS 2020 Inverse Reinforcement Learning from a Gradient-Based Learner Giorgia Ramponi, Gianluca Drappo, Marcello Restelli

IJCAI 2020 Risk-Averse Trust Region Optimization for Reward-Volatility Reduction Lorenzo Bisi, Luca Sabbioni, Edoardo Vittori, Matteo Papini, Marcello Restelli

ICML 2020 Sequential Transfer in Reinforcement Learning with a Generative Model Andrea Tirinzoni, Riccardo Poiani, Marcello Restelli

ICLR 2020 Sharing Knowledge in Multi-Task Deep Reinforcement Learning Carlo D'Eramo, Davide Tateo, Andrea Bonarini, Marcello Restelli, Jan Peters

JAIR 2020 Sliding-Window Thompson Sampling for Non-Stationary Settings Francesco Trovò, Marcello Restelli, Nicola Gatti

AISTATS 2020 Truly Batch Model-Free Inverse Reinforcement Learning About Multiple Intentions Giorgia Ramponi, Amarildo Likmeta, Alberto Maria Metelli, Andrea Tirinzoni, Marcello Restelli

ICML 2019 Optimistic Policy Optimization via Multiple Importance Sampling Matteo Papini, Alberto Maria Metelli, Lorenzo Lupo, Marcello Restelli

NeurIPS 2019 Propagating Uncertainty in Reinforcement Learning via Wasserstein Barycenters Alberto Maria Metelli, Amarildo Likmeta, Marcello Restelli

ICML 2019 Reinforcement Learning in Configurable Continuous Environments Alberto Maria Metelli, Emanuele Ghelfi, Marcello Restelli

ICML 2019 Transfer of Samples in Policy Search via Multiple Importance Sampling Andrea Tirinzoni, Mattia Salvini, Marcello Restelli

AAAI 2018 A Combinatorial-Bandit Algorithm for the Online Joint Bid/Budget Optimization of Pay-per-Click Advertising Campaigns Alessandro Nuara, Francesco Trovò, Nicola Gatti, Marcello Restelli

ICML 2018 Configurable Markov Decision Processes Alberto Maria Metelli, Mirco Mutti, Marcello Restelli

ICML 2018 Importance Weighted Transfer of Samples in Reinforcement Learning Andrea Tirinzoni, Andrea Sessa, Matteo Pirotta, Marcello Restelli

NeurIPS 2018 Policy Optimization via Importance Sampling Alberto Maria Metelli, Matteo Papini, Francesco Faccio, Marcello Restelli

ICML 2018 Stochastic Variance-Reduced Policy Gradient Matteo Papini, Damiano Binaghi, Giuseppe Canonaco, Matteo Pirotta, Marcello Restelli

NeurIPS 2018 Transfer of Value Functions via Variational Methods Andrea Tirinzoni, Rafael Rodriguez Sanchez, Marcello Restelli

NeurIPS 2017 Adaptive Batch Size for Safe Policy Gradients Matteo Papini, Matteo Pirotta, Marcello Restelli

ICML 2017 Boosted Fitted Q-Iteration Samuele Tosatto, Matteo Pirotta, Carlo D’Eramo, Marcello Restelli

NeurIPS 2017 Compatible Reward Inverse Reinforcement Learning Alberto Maria Metelli, Matteo Pirotta, Marcello Restelli

AAAI 2017 Estimating the Maximum Expected Value in Continuous Reinforcement Learning Problems Carlo D'Eramo, Alessandro Nuara, Matteo Pirotta, Marcello Restelli

UAI 2017 Regret Minimization Algorithms for the Followers Behaviour Identification in Leadership Games Lorenzo Bisi, Giuseppe De Nittis, Francesco Trovò, Marcello Restelli, Nicola Gatti

AAAI 2017 Unimodal Thompson Sampling for Graph-Structured Arms Stefano Paladino, Francesco Trovò, Marcello Restelli, Nicola Gatti

ICML 2016 Estimating Maximum Expected Value Through Gaussian Approximation Carlo D’Eramo, Marcello Restelli, Alessandro Nuara

AAAI 2016 Inverse Reinforcement Learning Through Policy Gradient Minimization Matteo Pirotta, Marcello Restelli

JAIR 2016 Multi-Objective Reinforcement Learning Through Continuous Pareto Manifold Approximation Simone Parisi, Matteo Pirotta, Marcello Restelli

AAAI 2016 Sequence-Form and Evolutionary Dynamics: Realization Equivalence to Agent Form and Logit Dynamics Nicola Gatti, Marcello Restelli

AAAI 2015 Multi-Objective Reinforcement Learning with Continuous Pareto Frontier Approximation Matteo Pirotta, Simone Parisi, Marcello Restelli

MLJ 2015 Policy Gradient in Lipschitz Markov Decision Processes Matteo Pirotta, Marcello Restelli, Luca Bascetta

AAAI 2014 Evolutionary Dynamics of Q-Learning over the Sequence Form Fabio Panozzo, Nicola Gatti, Marcello Restelli

NeurIPS 2014 Sparse Multi-Task Reinforcement Learning Daniele Calandriello, Alessandro Lazaric, Marcello Restelli

NeurIPS 2013 Adaptive Step-Size for Policy Gradient Methods Matteo Pirotta, Marcello Restelli, Luca Bascetta

AAAI 2013 Efficient Evolutionary Dynamics with Extensive-Form Games Nicola Gatti, Fabio Panozzo, Marcello Restelli

ICML 2013 Safe Policy Iteration Matteo Pirotta, Marcello Restelli, Alessio Pecorino, Daniele Calandriello

AAAI 2012 Computing Equilibria with Two-Player Zero-Sum Continuous Stochastic Games with Switching Controller Guido Bonomi, Nicola Gatti, Fabio Panozzo, Marcello Restelli

NeurIPS 2011 Transfer from Multiple MDPs Alessandro Lazaric, Marcello Restelli

ICML 2008 Transfer of Samples in Batch Reinforcement Learning Alessandro Lazaric, Marcello Restelli, Andrea Bonarini

NeurIPS 2007 Reinforcement Learning in Continuous Action Spaces Through Sequential Monte Carlo Methods Alessandro Lazaric, Marcello Restelli, Andrea Bonarini