Andrea Tirinzoni

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 47

Top Topics

Markov Decision Process

Reinforcement Learning

Top Venues

Publications

Matteo Pirotta, Andrea Tirinzoni, Ahmed Touati, Alessandro Lazaric, Yann Ollivier
Fast Imitation via Behavior Foundation Models. ICLR (2024)
Edoardo Cetin, Andrea Tirinzoni, Matteo Pirotta, Alessandro Lazaric, Yann Ollivier, Ahmed Touati
Simple Ingredients for Offline Reinforcement Learning. CoRR (2024)
Liyu Chen, Andrea Tirinzoni, Matteo Pirotta, Alessandro Lazaric
Reaching Goals is Hard: Settling the Sample Complexity of the Stochastic Shortest Path. ALT (2023)
Aymen Al Marjani, Andrea Tirinzoni, Emilie Kaufmann
Active Coverage for PAC Reinforcement Learning. COLT (2023)
Andrea Tirinzoni, Aymen Al Marjani, Emilie Kaufmann
Optimistic PAC Reinforcement Learning: the Instance-Dependent View. ALT (2023)
Liyu Chen, Andrea Tirinzoni, Alessandro Lazaric, Matteo Pirotta
Layered State Discovery for Incremental Autonomous Exploration. ICML (2023)
Aymen Al Marjani, Andrea Tirinzoni, Emilie Kaufmann
Towards Instance-Optimality in Online PAC Reinforcement Learning. CoRR (2023)
Aymen Al Marjani, Andrea Tirinzoni, Emilie Kaufmann
Active Coverage for PAC Reinforcement Learning. CoRR (2023)
Andrea Tirinzoni, Matteo Pirotta, Alessandro Lazaric
On the Complexity of Representation Learning in Contextual Linear Bandits. AISTATS (2023)
Liyu Chen, Andrea Tirinzoni, Alessandro Lazaric, Matteo Pirotta
Layered State Discovery for Incremental Autonomous Exploration. CoRR (2023)
Andrea Tirinzoni, Rémy Degenne
On Elimination Strategies for Bandit Fixed-Confidence Identification. CoRR (2022)
Andrea Tirinzoni, Matteo Papini, Ahmed Touati, Alessandro Lazaric, Matteo Pirotta
Scalable Representation Learning in Linear Contextual Bandits with Constant Regret Guarantees. NeurIPS (2022)
Andrea Tirinzoni, Rémy Degenne
On Elimination Strategies for Bandit Fixed-Confidence Identification. NeurIPS (2022)
Lorenzo Bisi, Davide Santambrogio, Federico Sandrelli, Andrea Tirinzoni, Brian D. Ziebart, Marcello Restelli
Risk-averse policy optimization via risk-neutral policy optimization. Artif. Intell. 311 (2022)
Andrea Tirinzoni, Matteo Papini, Ahmed Touati, Alessandro Lazaric, Matteo Pirotta
Scalable Representation Learning in Linear Contextual Bandits with Constant Regret Guarantees. CoRR (2022)
Liyu Chen, Andrea Tirinzoni, Matteo Pirotta, Alessandro Lazaric
Reaching Goals is Hard: Settling the Sample Complexity of the Stochastic Shortest Path. CoRR (2022)
Andrea Tirinzoni, Aymen Al Marjani, Emilie Kaufmann
Optimistic PAC Reinforcement Learning: the Instance-Dependent View. CoRR (2022)
Andrea Tirinzoni, Aymen Al Marjani, Emilie Kaufmann
Near Instance-Optimal PAC Reinforcement Learning for Deterministic MDPs. NeurIPS (2022)
Andrea Tirinzoni, Aymen Al Marjani, Emilie Kaufmann
Near Instance-Optimal PAC Reinforcement Learning for Deterministic MDPs. CoRR (2022)
Andrea Tirinzoni, Matteo Pirotta, Alessandro Lazaric
On the Complexity of Representation Learning in Contextual Linear Bandits. CoRR (2022)
Riccardo Poiani, Andrea Tirinzoni, Marcello Restelli
Meta-Reinforcement Learning by Tracking Task Non-stationarity. CoRR (2021)
Matteo Papini, Andrea Tirinzoni, Aldo Pacchiano, Marcello Restelli, Alessandro Lazaric, Matteo Pirotta
Reinforcement Learning in Linear MDPs: Constant Regret and Representation Selection. NeurIPS (2021)
Clémence Réda, Andrea Tirinzoni, Rémy Degenne
Dealing With Misspecification In Fixed-Confidence Linear Top-m Identification. NeurIPS (2021)
Matteo Papini, Andrea Tirinzoni, Marcello Restelli, Alessandro Lazaric, Matteo Pirotta
Leveraging Good Representations in Linear Contextual Bandits. CoRR (2021)
Clémence Réda, Andrea Tirinzoni, Rémy Degenne
Dealing With Misspecification In Fixed-Confidence Linear Top-m Identification. CoRR (2021)
Amarildo Likmeta, Alberto Maria Metelli, Giorgia Ramponi, Andrea Tirinzoni, Matteo Giuliani, Marcello Restelli
Dealing with multiple experts and non-stationarity in inverse reinforcement learning: an application to real-life problems. Mach. Learn. 110 (9) (2021)
Andrea Tirinzoni, Matteo Pirotta, Alessandro Lazaric
A Fully Problem-Dependent Regret Lower Bound for Finite-Horizon MDPs. CoRR (2021)
Matteo Papini, Andrea Tirinzoni, Aldo Pacchiano, Marcello Restelli, Alessandro Lazaric, Matteo Pirotta
Reinforcement Learning in Linear MDPs: Constant Regret and Representation Selection. CoRR (2021)
Riccardo Poiani, Andrea Tirinzoni, Marcello Restelli
Meta-Reinforcement Learning by Tracking Task Non-stationarity. IJCAI (2021)
Matteo Papini, Andrea Tirinzoni, Marcello Restelli, Alessandro Lazaric, Matteo Pirotta
Leveraging Good Representations in Linear Contextual Bandits. ICML (2021)
Andrea Tirinzoni, Alessandro Lazaric, Marcello Restelli
A Novel Confidence-Based Algorithm for Structured Bandits. AISTATS (2020)
Andrea Tirinzoni, Riccardo Poiani, Marcello Restelli
Sequential Transfer in Reinforcement Learning with a Generative Model. ICML (2020)
Giorgia Ramponi, Amarildo Likmeta, Alberto Maria Metelli, Andrea Tirinzoni, Marcello Restelli
Truly Batch Model-Free Inverse Reinforcement Learning about Multiple Intentions. AISTATS (2020)
Andrea Tirinzoni, Matteo Pirotta, Marcello Restelli, Alessandro Lazaric
An Asymptotically Optimal Primal-Dual Incremental Algorithm for Contextual Linear Bandits. NeurIPS (2020)
Andrea Tirinzoni, Riccardo Poiani, Marcello Restelli
Sequential Transfer in Reinforcement Learning with a Generative Model. CoRR (2020)
Andrea Tirinzoni, Alessandro Lazaric, Marcello Restelli
A Novel Confidence-Based Algorithm for Structured Bandits. CoRR (2020)
Pierluca D'Oro, Alberto Maria Metelli, Andrea Tirinzoni, Matteo Papini, Marcello Restelli
Gradient-Aware Model-Based Policy Search. AAAI (2020)
Andrea Tirinzoni, Matteo Pirotta, Marcello Restelli, Alessandro Lazaric
An Asymptotically Optimal Primal-Dual Incremental Algorithm for Contextual Linear Bandits. CoRR (2020)
Amarildo Likmeta, Alberto Maria Metelli, Andrea Tirinzoni, Riccardo Giol, Marcello Restelli, Danilo Romano
Combining reinforcement learning with rule-based controllers for transparent and general decision-making in autonomous driving. Robotics Auton. Syst. 131 (2020)
Mario Beraha, Alberto Maria Metelli, Matteo Papini, Andrea Tirinzoni, Marcello Restelli
Feature Selection via Mutual Information: New Theoretical Insights. CoRR (2019)
Mario Beraha, Alberto Maria Metelli, Matteo Papini, Andrea Tirinzoni, Marcello Restelli
Feature Selection via Mutual Information: New Theoretical Insights. IJCNN (2019)
Andrea Tirinzoni, Mattia Salvini, Marcello Restelli
Transfer of Samples in Policy Search via Multiple Importance Sampling. ICML (2019)
Pierluca D'Oro, Alberto Maria Metelli, Andrea Tirinzoni, Matteo Papini, Marcello Restelli
Gradient-Aware Model-based Policy Search. CoRR (2019)
Andrea Tirinzoni, Rafael Rodríguez-Sánchez, Marcello Restelli
Transfer of Value Functions via Variational Methods. NeurIPS (2018)
Andrea Tirinzoni, Marek Petrik, Xiangli Chen, Brian D. Ziebart
Policy-Conditioned Uncertainty Sets for Robust Markov Decision Processes. NeurIPS (2018)
Andrea Tirinzoni, Andrea Sessa, Matteo Pirotta, Marcello Restelli
Importance Weighted Transfer of Samples in Reinforcement Learning. ICML (2018)
Andrea Tirinzoni, Andrea Sessa, Matteo Pirotta, Marcello Restelli
Importance Weighted Transfer of Samples in Reinforcement Learning. CoRR (2018)