Andrea Tirinzoni

According to our database, Andrea Tirinzoni authored at least 29 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Simple Ingredients for Offline Reinforcement Learning.

Edoardo Cetin, Andrea Tirinzoni, Matteo Pirotta, Alessandro Lazaric, Yann Ollivier, Ahmed Touati

CoRR, 2024

2023

Towards Instance-Optimality in Online PAC Reinforcement Learning.

Aymen Al Marjani, Andrea Tirinzoni, Emilie Kaufmann

CoRR, 2023

Layered State Discovery for Incremental Autonomous Exploration.

Liyu Chen, Andrea Tirinzoni, Alessandro Lazaric, Matteo Pirotta

Proceedings of the International Conference on Machine Learning, 2023

Active Coverage for PAC Reinforcement Learning.

Aymen Al Marjani, Andrea Tirinzoni, Emilie Kaufmann

Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

Optimistic PAC Reinforcement Learning: the Instance-Dependent View.

Andrea Tirinzoni, Aymen Al Marjani, Emilie Kaufmann

Proceedings of the International Conference on Algorithmic Learning Theory, 2023

Reaching Goals is Hard: Settling the Sample Complexity of the Stochastic Shortest Path.

Liyu Chen, Andrea Tirinzoni, Matteo Pirotta, Alessandro Lazaric

Proceedings of the International Conference on Algorithmic Learning Theory, 2023

On the Complexity of Representation Learning in Contextual Linear Bandits.

Andrea Tirinzoni, Matteo Pirotta, Alessandro Lazaric

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Risk-averse policy optimization via risk-neutral policy optimization.

Lorenzo Bisi, Davide Santambrogio, Federico Sandrelli, Andrea Tirinzoni, Brian D. Ziebart, Marcello Restelli

Artif. Intell., 2022

Scalable Representation Learning in Linear Contextual Bandits with Constant Regret Guarantees.

Andrea Tirinzoni, Matteo Papini, Ahmed Touati, Alessandro Lazaric, Matteo Pirotta

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Near Instance-Optimal PAC Reinforcement Learning for Deterministic MDPs.

Andrea Tirinzoni, Aymen Al Marjani, Emilie Kaufmann

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

On Elimination Strategies for Bandit Fixed-Confidence Identification.

Andrea Tirinzoni, Rémy Degenne

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Exploiting structure for transfer in reinforcement learning.

Andrea Tirinzoni

PhD thesis, 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

A Fully Problem-Dependent Regret Lower Bound for Finite-Horizon MDPs.

Andrea Tirinzoni, Matteo Pirotta, Alessandro Lazaric

CoRR, 2021

Dealing With Misspecification In Fixed-Confidence Linear Top-m Identification.

Clémence Réda, Andrea Tirinzoni, Rémy Degenne

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Reinforcement Learning in Linear MDPs: Constant Regret and Representation Selection.

Matteo Papini, Andrea Tirinzoni, Aldo Pacchiano, Marcello Restelli, Alessandro Lazaric, Matteo Pirotta

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Meta-Reinforcement Learning by Tracking Task Non-stationarity.

Riccardo Poiani, Andrea Tirinzoni, Marcello Restelli

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Leveraging Good Representations in Linear Contextual Bandits.

Matteo Papini, Andrea Tirinzoni, Marcello Restelli, Alessandro Lazaric, Matteo Pirotta

Proceedings of the 38th International Conference on Machine Learning, 2021

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

An Asymptotically Optimal Primal-Dual Incremental Algorithm for Contextual Linear Bandits.

Andrea Tirinzoni, Matteo Pirotta, Marcello Restelli, Alessandro Lazaric

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Sequential Transfer in Reinforcement Learning with a Generative Model.

Andrea Tirinzoni, Riccardo Poiani, Marcello Restelli

Proceedings of the 37th International Conference on Machine Learning, 2020

A Novel Confidence-Based Algorithm for Structured Bandits.

Andrea Tirinzoni, Alessandro Lazaric, Marcello Restelli

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Truly Batch Model-Free Inverse Reinforcement Learning about Multiple Intentions.

Giorgia Ramponi, Amarildo Likmeta, Alberto Maria Metelli, Andrea Tirinzoni, Marcello Restelli

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Gradient-Aware Model-Based Policy Search.

Pierluca D'Oro, Alberto Maria Metelli, Andrea Tirinzoni, Matteo Papini, Marcello Restelli

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Feature Selection via Mutual Information: New Theoretical Insights.

Mario Beraha, Alberto Maria Metelli, Matteo Papini, Andrea Tirinzoni, Marcello Restelli

Proceedings of the International Joint Conference on Neural Networks, 2019

Transfer of Samples in Policy Search via Multiple Importance Sampling.

Andrea Tirinzoni, Mattia Salvini, Marcello Restelli

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

Transfer of Value Functions via Variational Methods.

Andrea Tirinzoni, Rafael Rodríguez-Sánchez, Marcello Restelli

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Policy-Conditioned Uncertainty Sets for Robust Markov Decision Processes.

Andrea Tirinzoni, Marek Petrik, Xiangli Chen, Brian D. Ziebart

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Importance Weighted Transfer of Samples in Reinforcement Learning.

Andrea Tirinzoni, Andrea Sessa, Matteo Pirotta, Marcello Restelli

Proceedings of the 35th International Conference on Machine Learning, 2018