| Feature selection via mutual information: New theoretical insights M Beraha, AM Metelli, M Papini, A Tirinzoni, M Restelli 2019 international joint conference on neural networks (IJCNN), 1-9, 2019 | 85 | 2019 |
| Combining reinforcement learning with rule-based controllers for transparent and general decision-making in autonomous driving A Likmeta, AM Metelli, A Tirinzoni, R Giol, M Restelli, D Romano Robotics and Autonomous Systems 131, 103568, 2020 | 72 | 2020 |
| Importance Weighted Transfer of Samples in Reinforcement Learning A Tirinzoni, A Sessa, M Pirotta, M Restelli International Conference on Machine Learning, 4936-4945, 2018 | 60 | 2018 |
| Gradient-aware model-based policy search P D'Oro, AM Metelli, A Tirinzoni, M Papini, M Restelli Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 3801-3808, 2020 | 43 | 2020 |
| An asymptotically optimal primal-dual incremental algorithm for contextual linear bandits A Tirinzoni, M Pirotta, M Restelli, A Lazaric Advances in Neural Information Processing Systems 33, 2021 | 41 | 2021 |
| Truly batch model-free inverse reinforcement learning about multiple intentions G Ramponi, A Likmeta, AM Metelli, A Tirinzoni, M Restelli International conference on artificial intelligence and statistics, 2359-2369, 2020 | 35 | 2020 |
| Transfer of samples in policy search via multiple importance sampling A Tirinzoni, M Salvini, M Restelli International Conference on Machine Learning, 6264-6274, 2019 | 31 | 2019 |
| Leveraging good representations in linear contextual bandits M Papini, A Tirinzoni, M Restelli, A Lazaric, M Pirotta International Conference on Machine Learning, 8371-8380, 2021 | 28 | 2021 |
| Dealing with multiple experts and non-stationarity in inverse reinforcement learning: an application to real-life problems A Likmeta, AM Metelli, G Ramponi, A Tirinzoni, M Giuliani, M Restelli Machine Learning 110, 2541-2576, 2021 | 24 | 2021 |
| Sequential transfer in reinforcement learning with a generative model A Tirinzoni, R Poiani, M Restelli International Conference on Machine Learning, 9481-9492, 2020 | 22 | 2020 |
| Transfer of value functions via variational methods A Tirinzoni, R Rodriguez Sanchez, M Restelli Advances in Neural Information Processing Systems 31, 2018 | 22 | 2018 |
| Policy-conditioned uncertainty sets for robust Markov decision processes A Tirinzoni, X Chen, M Petrik, B Ziebart Advances in Neural Information Processing Systems 31, 2018 | 21 | 2018 |
| Reinforcement learning in linear mdps: Constant regret and representation selection M Papini, A Tirinzoni, A Pacchiano, M Restelli, A Lazaric, M Pirotta Advances in Neural Information Processing Systems 34, 16371-16383, 2021 | 19 | 2021 |
| Near instance-optimal pac reinforcement learning for deterministic mdps A Tirinzoni, A Al Marjani, E Kaufmann Advances in neural information processing systems 35, 8785-8798, 2022 | 16 | 2022 |
| A novel confidence-based algorithm for structured bandits A Tirinzoni, A Lazaric, M Restelli International Conference on Artificial Intelligence and Statistics, 3175-3185, 2020 | 15 | 2020 |
| A fully problem-dependent regret lower bound for finite-horizon mdps A Tirinzoni, M Pirotta, A Lazaric arXiv preprint arXiv:2106.13013, 2021 | 14 | 2021 |
| Dealing with misspecification in fixed-confidence linear top-m identification C Réda, A Tirinzoni, R Degenne Advances in Neural Information Processing Systems 34, 25489-25501, 2021 | 11 | 2021 |
| Optimistic pac reinforcement learning: the instance-dependent view A Tirinzoni, A Al-Marjani, E Kaufmann International Conference on Algorithmic Learning Theory, 1460-1480, 2023 | 9 | 2023 |
| Meta-Reinforcement Learning by Tracking Task Non-stationarity R Poiani, A Tirinzoni, M Restelli Proceedings of the Thirtieth International Joint Conference on Artificial …, 2021 | 9 | 2021 |
| Active coverage for pac reinforcement learning A Al-Marjani, A Tirinzoni, E Kaufmann The Thirty Sixth Annual Conference on Learning Theory, 5044-5109, 2023 | 7 | 2023 |
Marcello RestelliAssociate Professor, Politecnico di Milano在 polimi.it 的电子邮件经过验证
