Mirco Mutti - RankMe

49 papers A* 17A 2Journal 29

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	K-Myriad: Jump-starting reinforcement learning with unsupervised parallel agents. CoRR Vincenzo De Paola, Mirco Mutti, Riccardo Zamboni, Marcello Restelli
2026	J	`jnl`	Unsupervised Behavioral Compression: Learning Low-Dimensional Policy Manifolds through State-Occupancy Matching. CoRR Andrea Fraschini, Davide Tenedini, Riccardo Zamboni, Mirco Mutti, Marcello Restelli
2025	A*	`conf`	A Classification View on Meta Learning Bandits. ICML Mirco Mutti, Jeongyeol Kwon, Shie Mannor, Aviv Tamar
2025	J	`jnl`	A Classification View on Meta Learning Bandits. CoRR Mirco Mutti, Jeongyeol Kwon, Shie Mannor, Aviv Tamar
2025	A*	`conf`	A Theoretical Framework for Partially-Observed Reward States in RLHF. ICLR Chinmaya Kausik, Mirco Mutti, Aldo Pacchiano, Ambuj Tewari
2025	J	`jnl`	Blindfolded Experts Generalize Better: Insights from Robotic Manipulation and Videogames. CoRR Ev Zisselman, Mirco Mutti, Shelly Francis-Meretzki, Elisei Shafer, Aviv Tamar
2025	A*	`conf`	Enhancing Diversity In Parallel Agents: A Maximum State Entropy Exploration Story. ICML Vincenzo De Paola, Riccardo Zamboni, Mirco Mutti, Marcello Restelli
2025	J	`jnl`	Enhancing Diversity in Parallel Agents: A Maximum State Entropy Exploration Story. CoRR Vincenzo De Paola, Riccardo Zamboni, Mirco Mutti, Marcello Restelli
2025	J	`jnl`	From Parameters to Behavior: Unsupervised Compression of the Policy Space. CoRR Davide Tenedini, Riccardo Zamboni, Mirco Mutti, Marcello Restelli
2025	J	`jnl`	Reward Compatibility: A Framework for Inverse RL. CoRR Filippo Lazzati, Mirco Mutti, Alberto Maria Metelli
2025	J	`jnl`	State Entropy Regularization for Robust Reinforcement Learning. CoRR Yonatan Ashlag, Uri Koren, Mirco Mutti, Esther Derman, Pierre-Luc Bacon, Shie Mannor
2025	J	`jnl`	Towards Principled Multi-Agent Task Agnostic Exploration. CoRR Riccardo Zamboni, Mirco Mutti, Marcello Restelli
2024	J	`jnl`	A Framework for Partially Observed Reward-States in RLHF. CoRR Chinmaya Kausik, Mirco Mutti, Aldo Pacchiano, Ambuj Tewari
2024	A*	`conf`	Exploiting Causal Graph Priors with Posterior Sampling for Reinforcement Learning. ICLR Mirco Mutti, Riccardo De Santi, Marcello Restelli, Alexander Marx, Giorgia Ramponi
2024	A*	`conf`	Geometric Active Exploration in Markov Decision Processes: the Benefit of Abstraction. ICML Riccardo De Santi, Federico Arangath Joseph, Noah Liniger, Mirco Mutti, Andreas Krause
2024	J	`jnl`	Geometric Active Exploration in Markov Decision Processes: the Benefit of Abstraction. CoRR Riccardo De Santi, Federico Arangath Joseph, Noah Liniger, Mirco Mutti, Andreas Krause
2024	A*	`conf`	How does Inverse RL Scale to Large State Spaces? A Provably Efficient Approach. NeurIPS Filippo Lazzati, Mirco Mutti, Alberto Maria Metelli
2024	A*	`conf`	How to Explore with Belief: State Entropy Maximization in POMDPs. ICML Riccardo Zamboni, Duilio Cirino, Marcello Restelli, Mirco Mutti
2024	J	`jnl`	How to Explore with Belief: State Entropy Maximization in POMDPs. CoRR Riccardo Zamboni, Duilio Cirino, Marcello Restelli, Mirco Mutti
2024	J	`jnl`	How to Scale Inverse RL to Large State Spaces? A Provably Efficient Approach. CoRR Filippo Lazzati, Mirco Mutti, Alberto Maria Metelli
2024	A*	`conf`	Offline Inverse RL: New Solution Concepts and Provably Efficient Algorithms. ICML Filippo Lazzati, Mirco Mutti, Alberto Maria Metelli
2024	J	`jnl`	Offline Inverse RL: New Solution Concepts and Provably Efficient Algorithms. CoRR Filippo Lazzati, Mirco Mutti, Alberto Maria Metelli
2024	A*	`conf`	Test-Time Regret Minimization in Meta Reinforcement Learning. ICML Mirco Mutti, Aviv Tamar
2024	J	`jnl`	Test-Time Regret Minimization in Meta Reinforcement Learning. CoRR Mirco Mutti, Aviv Tamar
2024	J	`jnl`	The Limits of Pure Exploration in POMDPs: When the Observation Entropy is Enough. RLJ Riccardo Zamboni, Duilio Cirino, Marcello Restelli, Mirco Mutti
2024	J	`jnl`	The Limits of Pure Exploration in POMDPs: When the Observation Entropy is Enough. CoRR Riccardo Zamboni, Duilio Cirino, Marcello Restelli, Mirco Mutti
2023	A	`conf`	A Tale of Sampling and Estimation in Discounted Reinforcement Learning. AISTATS Alberto Maria Metelli, Mirco Mutti, Marcello Restelli
2023	J	`jnl`	A Tale of Sampling and Estimation in Discounted Reinforcement Learning. CoRR Alberto Maria Metelli, Mirco Mutti, Marcello Restelli
2023	J	`jnl`	Convex Reinforcement Learning in Finite Trials. J. Mach. Learn. Res. Mirco Mutti, Riccardo De Santi, Piersilvio De Bartolomeis, Marcello Restelli
2023	J	`jnl`	Exploiting Causal Graph Priors with Posterior Sampling for Reinforcement Learning. CoRR Mirco Mutti, Riccardo De Santi, Marcello Restelli, Alexander Marx, Giorgia Ramponi
2023	A*	`conf`	Persuading Farsighted Receivers in MDPs: the Power of Honesty. NeurIPS Martino Bernasconi, Matteo Castiglioni, Alberto Marchesi, Mirco Mutti
2023	J	`jnl`	Persuading Farsighted Receivers in MDPs: the Power of Honesty. CoRR Martino Bernasconi, Matteo Castiglioni, Alberto Marchesi, Mirco Mutti
2023	A*	`conf`	Provably Efficient Causal Model-Based Reinforcement Learning for Systematic Generalization. AAAI Mirco Mutti, Riccardo De Santi, Emanuele Rossi, Juan Felipe Calderón, Michael M. Bronstein, Marcello Restelli
2023	—	`—`	Unsupervised reinforcement learning via state entropy maximization. Mirco Mutti
2022	A*	`conf`	Challenging Common Assumptions in Convex Reinforcement Learning. NeurIPS Mirco Mutti, Riccardo De Santi, Piersilvio De Bartolomeis, Marcello Restelli
2022	J	`jnl`	Challenging Common Assumptions in Convex Reinforcement Learning. CoRR Mirco Mutti, Riccardo De Santi, Piersilvio De Bartolomeis, Marcello Restelli
2022	J	`jnl`	Provably Efficient Causal Model-Based Reinforcement Learning for Systematic Generalization. CoRR Mirco Mutti, Riccardo De Santi, Emanuele Rossi, Juan Felipe Calderón, Michael M. Bronstein, Marcello Restelli
2022	A	`conf`	Reward-Free Policy Space Compression for Reinforcement Learning. AISTATS Mirco Mutti, Stefano Del Col, Marcello Restelli
2022	J	`jnl`	Reward-Free Policy Space Compression for Reinforcement Learning. CoRR Mirco Mutti, Stefano Del Col, Marcello Restelli
2022	A*	`conf`	The Importance of Non-Markovianity in Maximum State Entropy Exploration. ICML Mirco Mutti, Riccardo De Santi, Marcello Restelli
2022	J	`jnl`	The Importance of Non-Markovianity in Maximum State Entropy Exploration. CoRR Mirco Mutti, Riccardo De Santi, Marcello Restelli
2022	A*	`conf`	Unsupervised Reinforcement Learning in Multiple Environments. AAAI Mirco Mutti, Mattia Mancassola, Marcello Restelli
2021	A*	`conf`	Task-Agnostic Exploration via Policy Gradient of a Non-Parametric State Entropy Estimate. AAAI Mirco Mutti, Lorenzo Pratissoli, Marcello Restelli
2021	J	`jnl`	Unsupervised Reinforcement Learning in Multiple Environments. CoRR Mirco Mutti, Mattia Mancassola, Marcello Restelli
2020	J	`jnl`	A Policy Gradient Method for Task-Agnostic Exploration. CoRR Mirco Mutti, Lorenzo Pratissoli, Marcello Restelli
2020	A*	`conf`	An Intrinsically-Motivated Approach for Learning Highly Exploring and Fast Mixing Policies. AAAI Mirco Mutti, Marcello Restelli
2019	J	`jnl`	An Intrinsically-Motivated Approach for Learning Highly Exploring and Fast Mixing Policies. CoRR Mirco Mutti, Marcello Restelli
2018	A*	`conf`	Configurable Markov Decision Processes. ICML Alberto Maria Metelli, Mirco Mutti, Marcello Restelli
2018	J	`jnl`	Configurable Markov Decision Processes. CoRR Alberto Maria Metelli, Mirco Mutti, Marcello Restelli