Compatible Reward Inverse Reinforcement Learning. - Alberto Maria Metelli; Matteo Pirotta; Marcello Restelli (NIPS, 2017)

Configurable Markov Decision Processes. - Alberto Maria Metelli; Mirco Mutti; Marcello Restelli (ICML, 2018)

Policy Optimization via Importance Sampling. - Alberto Maria Metelli; Matteo Papini; Francesco Faccio; Marcello Restelli (NeurIPS, 2018)

Reinforcement Learning in Configurable Continuous Environments. - Alberto Maria Metelli; Emanuele Ghelfi; Marcello Restelli (ICML, 2019)

Optimistic Policy Optimization via Multiple Importance Sampling. - Matteo Papini; Alberto Maria Metelli; Lorenzo Lupo; Marcello Restelli (ICML, 2019)

Feature Selection via Mutual Information: New Theoretical Insights. - Mario Beraha; Alberto Maria Metelli; Matteo Papini; Andrea Tirinzoni; Marcello Restelli (IJCNN, 2019)

Propagating Uncertainty in Reinforcement Learning via Wasserstein Barycenters. - Alberto Maria Metelli; Amarildo Likmeta; Marcello Restelli (NeurIPS, 2019)

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

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

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

On the use of the policy gradient and Hessian in inverse reinforcement learning. - Alberto Maria Metelli; Matteo Pirotta; Marcello Restelli (Intelligenza Artificiale, 2020)

Importance Sampling Techniques for Policy Optimization. - Alberto Maria Metelli; Matteo Papini; Nico Montali; Marcello Restelli (J. Mach. Learn. Res., 2020)

Combining reinforcement learning with rule-based controllers for transparent and general decision-making in autonomous driving. - Amarildo Likmeta; Alberto Maria Metelli; Andrea Tirinzoni; Riccardo Giol; Marcello Restelli; Danilo Romano (Robotics Auton. Syst., 2020)

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

Provably Efficient Learning of Transferable Rewards. - Alberto Maria Metelli; Giorgia Ramponi; Alessandro Concetti; Marcello Restelli (ICML, 2021)

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

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

Safe Policy Iteration: A Monotonically Improving Approximate Policy Iteration Approach. - Alberto Maria Metelli; Matteo Pirotta; Daniele Calandriello; Marcello Restelli (J. Mach. Learn. Res., 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 (Mach. Learn., 2021)

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

Trust Region Meta Learning for Policy Optimization. - Manuel Occorso; Luca Sabbioni; Alberto Maria Metelli; Marcello Restelli (Meta-Knowledge Transfer @ ECML/PKDD, 2022)

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

Stochastic Rising Bandits. - Alberto Maria Metelli; Francesco Trovò; Matteo Pirola; Marcello Restelli (ICML, 2022)

Storehouse: a Reinforcement Learning Environment for Optimizing Warehouse Management. - Julen Cestero; Marco Quartulli; Alberto Maria Metelli; Marcello Restelli (IJCNN, 2022)

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

A unified view of configurable Markov Decision Processes: Solution concepts, value functions, and operators. - Alberto Maria Metelli (Intelligenza Artificiale, 2022)

Policy space identification in configurable environments. - Alberto Maria Metelli; Guglielmo Manneschi; Marcello Restelli (Mach. Learn., 2022)

Exploiting environment configurability in reinforcement learning. - Alberto Maria Metelli (IOS Press, 2022)

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

Tight Performance Guarantees of Imitator Policies with Continuous Actions. - Davide Maran; 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 (AAAI, 2023)

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

Towards Theoretical Understanding of Inverse Reinforcement Learning. - Alberto Maria Metelli; Filippo Lazzati; Marcello Restelli (ICML, 2023)

Dynamical Linear Bandits. - Marco Mussi; Alberto Maria Metelli; Marcello Restelli (ICML, 2023)

Truncating Trajectories in Monte Carlo Reinforcement Learning. - Riccardo Poiani; Alberto Maria Metelli; Marcello Restelli (ICML, 2023)

Information-Theoretic Regret Bounds for Bandits with Fixed Expert Advice. - Khaled Eldowa; Nicolò Cesa-Bianchi; Alberto Maria Metelli; Marcello Restelli (ITW, 2023)

Truncating Trajectories in Monte Carlo Policy Evaluation: an Adaptive Approach. - Riccardo Poiani; Nicole Nobili; Alberto Maria Metelli; Marcello Restelli (NeurIPS, 2023)

Distributional Policy Evaluation: a Maximum Entropy approach to Representation Learning. - Riccardo Zamboni; Alberto Maria Metelli; Marcello Restelli (NeurIPS, 2023)

On the Relation between Policy Improvement and Off-Policy Minimum-Variance Policy Evaluation. - Alberto Maria Metelli; Samuele Meta; Marcello Restelli (UAI, 2023)

An Option-Dependent Analysis of Regret Minimization Algorithms in Finite-Horizon Semi-Markov Decision Processes. - Gianluca Drappo; Alberto Maria Metelli; Marcello Restelli (CoRR, 2023)

Nonlinear Feature Aggregation: Two Algorithms driven by Theory. - Paolo Bonetti; Alberto Maria Metelli; Marcello Restelli (CoRR, 2023)

Pure Exploration under Mediators' Feedback. - Riccardo Poiani; Alberto Maria Metelli; Marcello Restelli (CoRR, 2023)

Towards Fully Adaptive Regret Minimization in Heavy-Tailed Bandits. - Gianmarco Genalti; Lupo Marsigli; Nicola Gatti 001; Alberto Maria Metelli (CoRR, 2023)

An Option-Dependent Analysis of Regret Minimization Algorithms in Finite-Horizon Semi-MDP. - Gianluca Drappo; Alberto Maria Metelli; Marcello Restelli (Trans. Mach. Learn. Res., 2023)

ARLO: A framework for Automated Reinforcement Learning. - Marco Mussi; Davide Lombarda; Alberto Maria Metelli; Francesco Trovò; Marcello Restelli (Expert Syst. Appl., 2023)

IWDA: Importance Weighting for Drift Adaptation in Streaming Supervised Learning Problems. - Filippo Fedeli; Alberto Maria Metelli; Francesco Trovò; Marcello Restelli (IEEE Trans. Neural Networks Learn. Syst., 2023)

Recent Advancements in Inverse Reinforcement Learning. - Alberto Maria Metelli (AAAI, 2024)

Parameterized Projected Bellman Operator. - Théo Vincent; Alberto Maria Metelli; Boris Belousov; Jan Peters 001; Marcello Restelli; Carlo D'Eramo (AAAI, 2024)

Autoregressive Bandits. - Francesco Bacchiocchi; Gianmarco Genalti; Davide Maran; Marco Mussi; Marcello Restelli; Nicola Gatti 001; Alberto Maria Metelli (AISTATS, 2024)

Dissimilarity Bandits. - Paolo Battellani; Alberto Maria Metelli; Francesco Trovò (AISTATS, 2024)

Transfer Learning for Dynamical Systems Models via Autoencoders and GANs. - Angelo Damiani; Gustavo Viera-López; Giorgio Manganini; Alberto Maria Metelli; Marcello Restelli (ACC, 2024)

(ε, u)-Adaptive Regret Minimization in Heavy-Tailed Bandits. - Gianmarco Genalti; Lupo Marsigli; Nicola Gatti 001; Alberto Maria Metelli (COLT, 2024)

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

Graph-Triggered Rising Bandits. - Gianmarco Genalti; Marco Mussi; Nicola Gatti 001; Marcello Restelli; Matteo Castiglioni; Alberto Maria Metelli (ICML, 2024)

Offline Inverse RL: New Solution Concepts and Provably Efficient Algorithms. - Filippo Lazzati; Mirco Mutti; Alberto Maria Metelli (ICML, 2024)

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

Learning Optimal Deterministic Policies with Stochastic Policy Gradients. - Alessandro Montenegro; Marco Mussi; Alberto Maria Metelli; Matteo Papini (ICML, 2024)

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

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

Online Learning with Off-Policy Feedback in Adversarial MDPs. - Francesco Bacchiocchi; Francesco Emanuele Stradi; Matteo Papini; Alberto Maria Metelli; Nicola Gatti 001 (IJCAI, 2024)

Causal Feature Selection via Transfer Entropy. - Paolo Bonetti; Alberto Maria Metelli; Marcello Restelli (IJCNN, 2024)

The Power of Hybrid Learning in Industrial Robotics: Efficient Grasping Strategies with Supervised-Driven Reinforcement Learning. - Vincenzo De Paola; Giuseppe Calcagno; Alberto Maria Metelli; Marcello Restelli (IJCNN, 2024)

How does Inverse RL Scale to Large State Spaces? A Provably Efficient Approach. - Filippo Lazzati; Mirco Mutti; Alberto Maria Metelli (NeurIPS, 2024)

Local Linearity: the Key for No-regret Reinforcement Learning in Continuous MDPs. - Davide Maran; Alberto Maria Metelli; Matteo Papini; Marcello Restelli (NeurIPS, 2024)

Last-Iterate Global Convergence of Policy Gradients for Constrained Reinforcement Learning. - Alessandro Montenegro; Marco Mussi; Matteo Papini; Alberto Maria Metelli (NeurIPS, 2024)

Sub-optimal Experts mitigate Ambiguity in Inverse Reinforcement Learning. - Riccardo Poiani; Gabriele Curti; Alberto Maria Metelli; Marcello Restelli (NeurIPS, 2024)

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

Interpetable Target-Feature Aggregation for Multi-task Learning Based on Bias-Variance Analysis. - Paolo Bonetti; Alberto Maria Metelli; Marcello Restelli (ECML/PKDD (6), 2024)

A Provably Efficient Option-Based Algorithm for both High-Level and Low-Level Learning. - Gianluca Drappo; Alberto Maria Metelli; Marcello Restelli (RLJ, 2024)

Policy Gradient with Active Importance Sampling. - Matteo Papini; Giorgio Manganini; Alberto Maria Metelli; Marcello Restelli (RLJ, 2024)

Inverse Reinforcement Learning with Sub-optimal Experts. - Riccardo Poiani; Gabriele Curti; Alberto Maria Metelli; Marcello Restelli (CoRR, 2024)

Information Capacity Regret Bounds for Bandits with Mediator Feedback. - Khaled Eldowa; Nicolò Cesa-Bianchi; Alberto Maria Metelli; Marcello Restelli (CoRR, 2024)

Performance Improvement Bounds for Lipschitz Configurable Markov Decision Processes. - Alberto Maria Metelli (CoRR, 2024)

How to Scale Inverse RL to Large State Spaces? A Provably Efficient Approach. - Filippo Lazzati; Mirco Mutti; Alberto Maria Metelli (CoRR, 2024)

Open Problem: Tight Bounds for Kernelized Multi-Armed Bandits with Bernoulli Rewards. - Marco Mussi; Simone Drago; Alberto Maria Metelli (CoRR, 2024)

State and Action Factorization in Power Grids. - Gianvito Losapio; Davide Beretta; Marco Mussi; Alberto Maria Metelli; Marcello Restelli (CoRR, 2024)

Sliding-Window Thompson Sampling for Non-Stationary Settings. - Marco Fiandri; Alberto Maria Metelli; Francesco Trovò (CoRR, 2024)

Bridging Rested and Restless Bandits with Graph-Triggering: Rising and Rotting. - Gianmarco Genalti; Marco Mussi; Nicola Gatti 001; Marcello Restelli; Matteo Castiglioni; Alberto Maria Metelli (CoRR, 2024)

Learning Utilities from Demonstrations in Markov Decision Processes. - Filippo Lazzati; Alberto Maria Metelli (CoRR, 2024)

Efficient Learning of POMDPs with Known Observation Model in Average-Reward Setting. - Alessio Russo; Alberto Maria Metelli; Marcello Restelli (CoRR, 2024)

Statistical Analysis of Policy Space Compression Problem. - Majid Molaei; Marcello Restelli; Alberto Maria Metelli; Matteo Papini (CoRR, 2024)

Rising Rested Bandits: Lower Bounds and Efficient Algorithms. - Marco Fiandri; Alberto Maria Metelli; Francesco Trovò (CoRR, 2024)

Switching Latent Bandits. - Alessio Russo; Alberto Maria Metelli; Marcello Restelli (Trans. Mach. Learn. Res., 2024)

Optimizing Empty Container Repositioning and Fleet Deployment via Configurable Semi-POMDPs. - Riccardo Poiani; Ciprian Stirbu; Alberto Maria Metelli; Marcello Restelli (IEEE Trans. Intell. Transp. Syst., 2024)

Interpretable linear dimensionality reduction based on bias-variance analysis. - Paolo Bonetti; Alberto Maria Metelli; Marcello Restelli (Data Min. Knowl. Discov., 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 (Mach. Learn., 2024)

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 (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)

Open Problem: Regret Minimization in Heavy-Tailed Bandits with Unknown Distributional Parameters. - Gianmarco Genalti; Alberto Maria Metelli (COLT, 2025)

Factored-reward bandits with intermediate observations: Regret minimization and best arm identification. - Marco Mussi; Simone Drago; Marcello Restelli; Alberto Maria Metelli (Artif. Intell., 2025)

AReS: A patient simulator to facilitate testing of automated anesthesia. - Sara Hosseinirad; Manuela Merlo; Francesco Trovò; Emiliano Tognoli; Alberto Maria Metelli; Guy Albert Dumont (Comput. Methods Programs Biomed., 2025)

Generalizing the Regret: an Analysis of Lower and Upper Bounds. - Marco Mussi; Alberto Maria Metelli (J. Artif. Intell. Res., 2025)

On the Partial Identifiability in Reward Learning: Choosing the Best Reward. - Filippo Lazzati; Alberto Maria Metelli (CoRR, 2025)

Reward Compatibility: A Framework for Inverse RL. - Filippo Lazzati; Mirco Mutti; Alberto Maria Metelli (CoRR, 2025)

Achieving O(√T) Regret in Average-Reward POMDPs with Known Observation Models. - Alessio Russo; Alberto Maria Metelli; Marcello Restelli (CoRR, 2025)

A Refined Analysis of UCBVI. - Simone Drago; Marco Mussi; Alberto Maria Metelli (CoRR, 2025)

Thompson Sampling-like Algorithms for Stochastic Rising Bandits. - Marco Fiandri; Alberto Maria Metelli; Francesco Trovò (CoRR, 2025)

Catoni-Style Change Point Detection for Regret Minimization in Non-Stationary Heavy-Tailed Bandits. - Gianmarco Genalti; Sujay Bhatt; Nicola Gatti 001; Alberto Maria Metelli (CoRR, 2025)

Learning Deterministic Policies with Policy Gradients in Constrained Markov Decision Processes. - Alessandro Montenegro; Leonardo Cesani; Marco Mussi; Matteo Papini; Alberto Maria Metelli (CoRR, 2025)

Reusing Trajectories in Policy Gradients Enables Fast Convergence. - Alessandro Montenegro; Federico Mansutti; Marco Mussi; Matteo Papini; Alberto Maria Metelli (CoRR, 2025)

Gym4ReaL: A Suite for Benchmarking Real-World Reinforcement Learning. - Davide Salaorni; Vincenzo De Paola; Samuele Delpero; Giovanni Dispoto; Paolo Bonetti; Alessio Russo; Giuseppe Calcagno; Francesco Trovò; Matteo Papini; Alberto Maria Metelli; Marco Mussi; Marcello Restelli (CoRR, 2025)

Generalized Kernelized Bandits: Self-Normalized Bernstein-Like Dimension-Free Inequality and Regret Bounds. - Alberto Maria Metelli; Simone Drago; Marco Mussi (CoRR, 2025)

Search or split: policy gradient with adaptive policy space. - Gianmarco Tedeschi; Matteo Papini; Alberto Maria Metelli; Marcello Restelli (Mach. Learn., 2025)