| Sliding-window thompson sampling for non-stationary settings F Trovo, S Paladino, M Restelli, N Gatti Journal of Artificial Intelligence Research 68, 311-364, 2020 | 80 | 2020 |
| Improving multi-armed bandit algorithms in online pricing settings F Trovò, S Paladino, M Restelli, N Gatti International Journal of Approximate Reasoning 98, 196-235, 2018 | 42 | 2018 |
| Unimodal thompson sampling for graph-structured arms S Paladino, F Trovo, M Restelli, N Gatti Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017 | 41 | 2017 |
| Multi-armed bandit for pricing F Trovo, S Paladino, M Restelli, N Gatti Proceedings of the 12th European Workshop on Reinforcement Learning, 1-9, 2015 | 33 | 2015 |
| Budgeted Multi–Armed Bandit in Continuous Action Space F Trovo, S Paladino, M Restelli, N Gatti Frontiers in Artificial Intelligence and Applications (Proceedings of the …, 2016 | 30 | 2016 |
| Improving multi-armed bandit algorithms for pricing F Trovo, S Paladino, M Restelli, N Gatti 16th European Conference on Multi-Agent Systems, 1-15, 2018 | 3 | 2018 |
| Risk-averse trees for learning from logged bandit feedback F Trovò, S Paladino, P Simone, M Restelli, N Gatti 2017 International Joint Conference on Neural Networks (IJCNN), 976-983, 2017 | 2 | 2017 |
| A learning approach for pricing in e-commerce scenario S Paladino Politecnico di Milano, 2018 | | 2018 |
| Algorithms for verification and computation of strong Nash equilibria S Paladino Politecnico di Milano, 2013 | | 2013 |
Francesco TrovòPolitecnico di Milano, Dipartimento di Elettronica, Informazione e BioingegneriaPatvirtintas el. paštas polimi.it