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Matteo Pirotta
Matteo Pirotta
Research Scientist, Meta (FAIR)
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Vuosi
Stochastic variance-reduced policy gradient
M Papini, D Binaghi, G Canonaco, M Pirotta, M Restelli
International conference on machine learning, 4026-4035, 2018
1752018
Exploration-exploitation in constrained mdps
Y Efroni, S Mannor, M Pirotta
arXiv preprint arXiv:2003.02189, 2020
1402020
Frequentist regret bounds for randomized least-squares value iteration
A Zanette, D Brandfonbrener, E Brunskill, M Pirotta, A Lazaric
International Conference on Artificial Intelligence and Statistics, 1954-1964, 2020
1332020
Safe policy iteration
M Pirotta, M Restelli, A Pecorino, D Calandriello
International Conference on Machine Learning, 307-315, 2013
1172013
Efficient bias-span-constrained exploration-exploitation in reinforcement learning
R Fruit, M Pirotta, A Lazaric, R Ortner
International Conference on Machine Learning, 1578-1586, 2018
1052018
Policy gradient in lipschitz markov decision processes
M Pirotta, M Restelli, L Bascetta
Machine Learning 100, 255-283, 2015
992015
Adaptive step-size for policy gradient methods
M Pirotta, M Restelli, L Bascetta
Advances in Neural Information Processing Systems 26, 2013
842013
Multi-objective reinforcement learning with continuous pareto frontier approximation
M Pirotta, S Parisi, M Restelli
Proceedings of the AAAI conference on artificial intelligence 29 (1), 2015
702015
Policy gradient approaches for multi-objective sequential decision making
S Parisi, M Pirotta, N Smacchia, L Bascetta, M Restelli
2014 International Joint Conference on Neural Networks (IJCNN), 2323-2330, 2014
682014
Multi-objective reinforcement learning through continuous pareto manifold approximation
S Parisi, M Pirotta, M Restelli
Journal of Artificial Intelligence Research 57, 187-227, 2016
562016
Importance weighted transfer of samples in reinforcement learning
A Tirinzoni, A Sessa, M Pirotta, M Restelli
International Conference on Machine Learning, 4936-4945, 2018
552018
Inverse reinforcement learning through policy gradient minimization
M Pirotta, M Restelli
Proceedings of the AAAI Conference on Artificial Intelligence 30 (1), 2016
552016
Adversarial attacks on linear contextual bandits
E Garcelon, B Roziere, L Meunier, J Tarbouriech, O Teytaud, A Lazaric, ...
Advances in Neural Information Processing Systems 33, 14362-14373, 2020
532020
Near optimal exploration-exploitation in non-communicating markov decision processes
R Fruit, M Pirotta, A Lazaric
Advances in Neural Information Processing Systems 31, 2018
472018
Boosted fitted q-iteration
S Tosatto, M Pirotta, C d’Eramo, M Restelli
International Conference on Machine Learning, 3434-3443, 2017
462017
Regret bounds for kernel-based reinforcement learning
OD Domingues, P Ménard, M Pirotta, E Kaufmann, M Valko
arXiv preprint arXiv:2004.05599, 2020
45*2020
Adaptive batch size for safe policy gradients
M Papini, M Pirotta, M Restelli
Advances in neural information processing systems 30, 2017
452017
Manifold-based multi-objective policy search with sample reuse
S Parisi, M Pirotta, J Peters
Neurocomputing 263, 3-14, 2017
442017
Compatible reward inverse reinforcement learning
AM Metelli, M Pirotta, M Restelli
Advances in neural information processing systems 30, 2017
442017
No-regret exploration in goal-oriented reinforcement learning
J Tarbouriech, E Garcelon, M Valko, M Pirotta, A Lazaric
International Conference on Machine Learning, 9428-9437, 2020
402020
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