Tirinzoni, Andrea

29 publications

ICML 2025 Temporal Difference Flows Jesse Farebrother, Matteo Pirotta, Andrea Tirinzoni, Remi Munos, Alessandro Lazaric, Ahmed Touati

ICLRW 2025 Temporal Difference Flows Jesse Farebrother, Matteo Pirotta, Andrea Tirinzoni, Remi Munos, Alessandro Lazaric, Ahmed Touati

ICLR 2025 Zero-Shot Whole-Body Humanoid Control via Behavioral Foundation Models Andrea Tirinzoni, Ahmed Touati, Jesse Farebrother, Mateusz Guzek, Anssi Kanervisto, Yingchen Xu, Alessandro Lazaric, Matteo Pirotta

ICLR 2024 Fast Imitation via Behavior Foundation Models Matteo Pirotta, Andrea Tirinzoni, Ahmed Touati, Alessandro Lazaric, Yann Ollivier

ICML 2024 Simple Ingredients for Offline Reinforcement Learning Edoardo Cetin, Andrea Tirinzoni, Matteo Pirotta, Alessandro Lazaric, Yann Ollivier, Ahmed Touati

NeurIPSW 2024 Zero-Shot Whole-Body Humanoid Control via Behavioral Foundation Models Andrea Tirinzoni, Ahmed Touati, Jesse Farebrother, Mateusz Guzek, Anssi Kanervisto, Yingchen Xu, Alessandro Lazaric, Matteo Pirotta

COLT 2023 Active Coverage for PAC Reinforcement Learning Aymen Al-Marjani, Andrea Tirinzoni, Emilie Kaufmann

NeurIPSW 2023 Fast Imitation via Behavior Foundation Models Matteo Pirotta, Andrea Tirinzoni, Ahmed Touati, Alessandro Lazaric, Yann Ollivier

ICML 2023 Layered State Discovery for Incremental Autonomous Exploration Liyu Chen, Andrea Tirinzoni, Alessandro Lazaric, Matteo Pirotta

AISTATS 2023 On the Complexity of Representation Learning in Contextual Linear Bandits Andrea Tirinzoni, Matteo Pirotta, Alessandro Lazaric

ALT 2023 Optimistic PAC Reinforcement Learning: The Instance-Dependent View Andrea Tirinzoni, Aymen Al-Marjani, Emilie Kaufmann

ALT 2023 Reaching Goals Is Hard: Settling the Sample Complexity of the Stochastic Shortest Path Liyu Chen, Andrea Tirinzoni, Matteo Pirotta, Alessandro Lazaric

NeurIPS 2022 Near Instance-Optimal PAC Reinforcement Learning for Deterministic MDPs Andrea Tirinzoni, Aymen Al Marjani, Emilie Kaufmann

NeurIPS 2022 On Elimination Strategies for Bandit Fixed-Confidence Identification Andrea Tirinzoni, Rémy Degenne

NeurIPS 2022 Scalable Representation Learning in Linear Contextual Bandits with Constant Regret Guarantees Andrea Tirinzoni, Matteo Papini, Ahmed Touati, Alessandro Lazaric, Matteo Pirotta

NeurIPS 2021 Dealing with Misspecification in Fixed-Confidence Linear Top-M Identification Clémence Réda, Andrea Tirinzoni, Rémy Degenne

MLJ 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

ICML 2021 Leveraging Good Representations in Linear Contextual Bandits Matteo Papini, Andrea Tirinzoni, Marcello Restelli, Alessandro Lazaric, Matteo Pirotta

IJCAI 2021 Meta-Reinforcement Learning by Tracking Task Non-Stationarity Riccardo Poiani, Andrea Tirinzoni, Marcello Restelli

NeurIPS 2021 Reinforcement Learning in Linear MDPs: Constant Regret and Representation Selection Matteo Papini, Andrea Tirinzoni, Aldo Pacchiano, Marcello Restelli, Alessandro Lazaric, Matteo Pirotta

AISTATS 2020 A Novel Confidence-Based Algorithm for Structured Bandits Andrea Tirinzoni, Alessandro Lazaric, Marcello Restelli

NeurIPS 2020 An Asymptotically Optimal Primal-Dual Incremental Algorithm for Contextual Linear Bandits Andrea Tirinzoni, Matteo Pirotta, Marcello Restelli, Alessandro Lazaric

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

ICML 2020 Sequential Transfer in Reinforcement Learning with a Generative Model Andrea Tirinzoni, Riccardo Poiani, Marcello Restelli

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

ICML 2019 Transfer of Samples in Policy Search via Multiple Importance Sampling Andrea Tirinzoni, Mattia Salvini, Marcello Restelli

ICML 2018 Importance Weighted Transfer of Samples in Reinforcement Learning Andrea Tirinzoni, Andrea Sessa, Matteo Pirotta, Marcello Restelli

NeurIPS 2018 Policy-Conditioned Uncertainty Sets for Robust Markov Decision Processes Andrea Tirinzoni, Marek Petrik, Xiangli Chen, Brian Ziebart

NeurIPS 2018 Transfer of Value Functions via Variational Methods Andrea Tirinzoni, Rafael Rodriguez Sanchez, Marcello Restelli