Matteo Papini - RankMe

61 papers A* 19A 2B 3Journal 34Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Do It for HER: First-Order Temporal Logic Reward Specification in Reinforcement Learning (Extended Version). CoRR Pierriccardo Olivieri, Fausto Lasca, Alessandro Gianola, Matteo Papini
2026	A*	`conf`	Do It for HER: First-Order Temporal Logic Reward Specification in Reinforcement Learning. AAAI Pierriccardo Olivieri, Fausto Lasca, Alessandro Gianola, Matteo Papini
2026	J	`jnl`	How Log-Barrier Helps Exploration in Policy Optimization. CoRR Leonardo Cesani, Matteo Papini, Marcello Restelli
2026	J	`jnl`	Impact of Connectivity on Laplacian Representations in Reinforcement Learning. CoRR Tommaso Giorgi, Pierriccardo Olivieri, Keyue Jiang, Laura Toni, Matteo Papini
2025	J	`jnl`	Balancing Benefits and Risks: RL Approaches for Addiction-Aware Social Media Recommenders. CoRR Luca Bolis, Stefano Livella, Sabrina Patania, Dimitri Ognibene, Matteo Papini, Kenji Morita
2025	A*	`conf`	Convergence Analysis of Policy Gradient Methods with Dynamic Stochasticity. ICML Alessandro Montenegro, Marco Mussi, Matteo Papini, Alberto Maria Metelli
2025	J	`jnl`	Gym4ReaL: A Suite for Benchmarking Real-World Reinforcement Learning. CoRR 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
2025	J	`jnl`	Learning Deterministic Policies with Policy Gradients in Constrained Markov Decision Processes. CoRR Alessandro Montenegro, Leonardo Cesani, Marco Mussi, Matteo Papini, Alberto Maria Metelli
2025	J	`jnl`	Reusing Trajectories in Policy Gradients Enables Fast Convergence. CoRR Alessandro Montenegro, Federico Mansutti, Marco Mussi, Matteo Papini, Alberto Maria Metelli
2025	J	`jnl`	Search or split: policy gradient with adaptive policy space. Mach. Learn. Gianmarco Tedeschi, Matteo Papini, Alberto Maria Metelli, Marcello Restelli
2024	B	`conf`	Importance-Weighted Offline Learning Done Right. ALT Germano Gabbianelli, Gergely Neu, Matteo Papini
2024	A*	`conf`	Last-Iterate Global Convergence of Policy Gradients for Constrained Reinforcement Learning. NeurIPS Alessandro Montenegro, Marco Mussi, Matteo Papini, Alberto Maria Metelli
2024	J	`jnl`	Last-Iterate Global Convergence of Policy Gradients for Constrained Reinforcement Learning. CoRR Alessandro Montenegro, Marco Mussi, Matteo Papini, Alberto Maria Metelli
2024	A*	`conf`	Learning Optimal Deterministic Policies with Stochastic Policy Gradients. ICML Alessandro Montenegro, Marco Mussi, Alberto Maria Metelli, Matteo Papini
2024	J	`jnl`	Learning Optimal Deterministic Policies with Stochastic Policy Gradients. CoRR Alessandro Montenegro, Marco Mussi, Alberto Maria Metelli, Matteo Papini
2024	A*	`conf`	Local Linearity: the Key for No-regret Reinforcement Learning in Continuous MDPs. NeurIPS Davide Maran, Alberto Maria Metelli, Matteo Papini, Marcello Restelli
2024	J	`jnl`	Local Linearity: the Key for No-regret Reinforcement Learning in Continuous MDPs. CoRR Davide Maran, Alberto Maria Metelli, Matteo Papini, Marcello Restelli
2024	A*	`conf`	No-Regret Reinforcement Learning in Smooth MDPs. ICML Davide Maran, Alberto Maria Metelli, Matteo Papini, Marcello Restelli
2024	J	`jnl`	No-Regret Reinforcement Learning in Smooth MDPs. CoRR Davide Maran, Alberto Maria Metelli, Matteo Papini, Marcello Restelli
2024	A	`conf`	Offline Primal-Dual Reinforcement Learning for Linear MDPs. AISTATS Germano Gabbianelli, Gergely Neu, Matteo Papini, Nneka Okolo
2024	A*	`conf`	Online Learning with Off-Policy Feedback in Adversarial MDPs. IJCAI Francesco Bacchiocchi, Francesco Emanuele Stradi, Matteo Papini, Alberto Maria Metelli, Nicola Gatti
2024	A*	`conf`	Optimistic Information Directed Sampling. COLT Gergely Neu, Matteo Papini, Ludovic Schwartz
2024	J	`jnl`	Optimistic Information Directed Sampling. CoRR Gergely Neu, Matteo Papini, Ludovic Schwartz
2024	J	`jnl`	Policy Gradient with Active Importance Sampling. RLJ Matteo Papini, Giorgio Manganini, Alberto Maria Metelli, Marcello Restelli
2024	J	`jnl`	Policy Gradient with Active Importance Sampling. CoRR Matteo Papini, Giorgio Manganini, Alberto Maria Metelli, Marcello Restelli
2024	A*	`conf`	Projection by Convolution: Optimal Sample Complexity for Reinforcement Learning in Continuous-Space MDPs. COLT Davide Maran, Alberto Maria Metelli, Matteo Papini, Marcello Restelli
2024	J	`jnl`	Projection by Convolution: Optimal Sample Complexity for Reinforcement Learning in Continuous-Space MDPs. CoRR Davide Maran, Alberto Maria Metelli, Matteo Papini, Marcello Restelli
2024	J	`jnl`	Sample complexity of variance-reduced policy gradient: weaker assumptions and lower bounds. Mach. Learn. Gabor Paczolay, Matteo Papini, Alberto Maria Metelli, István Á. Harmati, Marcello Restelli
2024	J	`jnl`	Statistical Analysis of Policy Space Compression Problem. CoRR Majid Molaei, Marcello Restelli, Alberto Maria Metelli, Matteo Papini
2023	J	`jnl`	Importance-Weighted Offline Learning Done Right. CoRR Germano Gabbianelli, Gergely Neu, Matteo Papini
2023	J	`jnl`	Offline Primal-Dual Reinforcement Learning for Linear MDPs. CoRR Germano Gabbianelli, Gergely Neu, Nneka Okolo, Matteo Papini
2023	B	`conf`	Online Learning with Off-Policy Feedback. ALT Germano Gabbianelli, Gergely Neu, Matteo Papini
2022	A*	`conf`	Lifting the Information Ratio: An Information-Theoretic Analysis of Thompson Sampling for Contextual Bandits. NeurIPS Gergely Neu, Julia Olkhovskaya, Matteo Papini, Ludovic Schwartz
2022	J	`jnl`	Lifting the Information Ratio: An Information-Theoretic Analysis of Thompson Sampling for Contextual Bandits. CoRR Gergely Neu, Julia Olkhovskaya, Matteo Papini, Ludovic Schwartz
2022	J	`jnl`	Online Learning with Off-Policy Feedback. CoRR Germano Gabbianelli, Matteo Papini, Gergely Neu
2022	A*	`conf`	Scalable Representation Learning in Linear Contextual Bandits with Constant Regret Guarantees. NeurIPS Andrea Tirinzoni, Matteo Papini, Ahmed Touati, Alessandro Lazaric, Matteo Pirotta
2022	J	`jnl`	Scalable Representation Learning in Linear Contextual Bandits with Constant Regret Guarantees. CoRR Andrea Tirinzoni, Matteo Papini, Ahmed Touati, Alessandro Lazaric, Matteo Pirotta
2022	J	`jnl`	Smoothing policies and safe policy gradients. Mach. Learn. Matteo Papini, Matteo Pirotta, Marcello Restelli
2021	—	`conf`	Automated Reasoning for Reinforcement Learning Agents in Structured Environments. OVERLAY@GandALF Alessandro Gianola, Marco Montali, Matteo Papini
2021	A*	`conf`	Leveraging Good Representations in Linear Contextual Bandits. ICML Matteo Papini, Andrea Tirinzoni, Marcello Restelli, Alessandro Lazaric, Matteo Pirotta
2021	J	`jnl`	Leveraging Good Representations in Linear Contextual Bandits. CoRR Matteo Papini, Andrea Tirinzoni, Marcello Restelli, Alessandro Lazaric, Matteo Pirotta
2021	A*	`conf`	Policy Optimization as Online Learning with Mediator Feedback. AAAI Alberto Maria Metelli, Matteo Papini, Pierluca D'Oro, Marcello Restelli
2021	A*	`conf`	Reinforcement Learning in Linear MDPs: Constant Regret and Representation Selection. NeurIPS Matteo Papini, Andrea Tirinzoni, Aldo Pacchiano, Marcello Restelli, Alessandro Lazaric, Matteo Pirotta
2021	J	`jnl`	Reinforcement Learning in Linear MDPs: Constant Regret and Representation Selection. CoRR Matteo Papini, Andrea Tirinzoni, Aldo Pacchiano, Marcello Restelli, Alessandro Lazaric, Matteo Pirotta
2021	—	`—`	Safe policy optimization. Matteo Papini
2020	A	`conf`	Balancing Learning Speed and Stability in Policy Gradient via Adaptive Exploration. AISTATS Matteo Papini, Andrea Battistello, Marcello Restelli
2020	A*	`conf`	Gradient-Aware Model-Based Policy Search. AAAI Pierluca D'Oro, Alberto Maria Metelli, Andrea Tirinzoni, Matteo Papini, Marcello Restelli
2020	J	`jnl`	Importance Sampling Techniques for Policy Optimization. J. Mach. Learn. Res. Alberto Maria Metelli, Matteo Papini, Nico Montali, Marcello Restelli
2020	J	`jnl`	Policy Optimization as Online Learning with Mediator Feedback. CoRR Alberto Maria Metelli, Matteo Papini, Pierluca D'Oro, Marcello Restelli
2020	A*	`conf`	Risk-Averse Trust Region Optimization for Reward-Volatility Reduction. IJCAI Lorenzo Bisi, Luca Sabbioni, Edoardo Vittori, Matteo Papini, Marcello Restelli
2019	B	`conf`	Feature Selection via Mutual Information: New Theoretical Insights. IJCNN Mario Beraha, Alberto Maria Metelli, Matteo Papini, Andrea Tirinzoni, Marcello Restelli
2019	J	`jnl`	Feature Selection via Mutual Information: New Theoretical Insights. CoRR Mario Beraha, Alberto Maria Metelli, Matteo Papini, Andrea Tirinzoni, Marcello Restelli
2019	J	`jnl`	Gradient-Aware Model-based Policy Search. CoRR Pierluca D'Oro, Alberto Maria Metelli, Andrea Tirinzoni, Matteo Papini, Marcello Restelli
2019	A*	`conf`	Optimistic Policy Optimization via Multiple Importance Sampling. ICML Matteo Papini, Alberto Maria Metelli, Lorenzo Lupo, Marcello Restelli
2019	J	`jnl`	Risk-Averse Trust Region Optimization for Reward-Volatility Reduction. CoRR Lorenzo Bisi, Luca Sabbioni, Edoardo Vittori, Matteo Papini, Marcello Restelli
2019	J	`jnl`	Smoothing Policies and Safe Policy Gradients. CoRR Matteo Papini, Matteo Pirotta, Marcello Restelli
2018	A*	`conf`	Policy Optimization via Importance Sampling. NeurIPS Alberto Maria Metelli, Matteo Papini, Francesco Faccio, Marcello Restelli
2018	J	`jnl`	Policy Optimization via Importance Sampling. CoRR Alberto Maria Metelli, Matteo Papini, Francesco Faccio, Marcello Restelli
2018	A*	`conf`	Stochastic Variance-Reduced Policy Gradient. ICML Matteo Papini, Damiano Binaghi, Giuseppe Canonaco, Matteo Pirotta, Marcello Restelli
2018	J	`jnl`	Stochastic Variance-Reduced Policy Gradient. CoRR Matteo Papini, Damiano Binaghi, Giuseppe Canonaco, Matteo Pirotta, Marcello Restelli
2017	—	`conf`	Adaptive Batch Size for Safe Policy Gradients. NIPS Matteo Papini, Matteo Pirotta, Marcello Restelli