Marcello Restelli

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	All	Since 2017
Citations	3231	2295
h-index	30	27
i10-index	84	70

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Andrea BonariniFull Professor, Politecnico di MilanoVerified email at polimi.it
Alessandro LazaricResearch Scientist, Facebook Artificial Intelligence ResearchVerified email at inria.fr
Matteo PirottaResearch Scientist, Facebook AI ResearchVerified email at fb.com
Alberto Maria MetelliPostdoctoral Researcher, Politecnico di MilanoVerified email at polimi.it
Nicola GattiPolitecnico di MilanoVerified email at elet.polimi.it
Matteo MatteucciFull Professor, Department of Electronics Information and Bioengineering, Politecnico di MilanoVerified email at polimi.it
Francesco TrovòPolitecnico di MilanoVerified email at polimi.it
Andrea CastellettiProfessor, Politecnico di MilanoVerified email at polimi.it
Matteo PapiniPolitecnico di MilanoVerified email at polimi.it
Andrea TirinzoniFacebook AI ResearchVerified email at fb.com
Alessandro NuaraPhD student, Politecnico di MilanoVerified email at polimi.it
Stefano GalelliAssociate Professor, Singapore University of Technology and DesignVerified email at sutd.edu.sg
Carlo D'EramoIndependent Research Group Leader - LiteRL @ Hessian.AI | TU DarmstadtVerified email at robot-learning.de
Luca BascettaAssociate Professor, Department of Electronics Information and Bioengineering, Politecnico di MilanoVerified email at polimi.it
Mirco MuttiPolitecnico di MilanoVerified email at polimi.it
Stefano PaladinoPolitecnico di MilanoVerified email at polimi.it
Enrique Munoz de CoteProfessor of Computer Science at INAOE; CSO @ People & AI; past: Director at SecondmindVerified email at people-ai.com
Lorenzo BisiPhD student, Politecnico di MilanoVerified email at polimi.it
Domenico Giorgio SorrentiUniversità degli Studi di Milano - BicoccaVerified email at unimib.it
Edoardo VittoriPhd Student, Politecnico di MilanoVerified email at polimi.it

Marcello Restelli

Associate Professor, Politecnico di Milano

Verified email at polimi.it - Homepage

Machine Learning Reinforcement Learning


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Tree‐based reinforcement learning for optimal water reservoir operation A Castelletti, S Galelli, M Restelli, R Soncini‐Sessa Water Resources Research 46 (9), 2010	178	2010
Transfer of samples in batch reinforcement learning A Lazaric, M Restelli, A Bonarini Proceedings of the 25th international conference on Machine learning, 544-551, 2008	165	2008
Reinforcement learning in continuous action spaces through sequential Monte Carlo methods A Lazaric, M Restelli, A Bonarini In: Adv. Neural Information Proc. Systems, 2007	147	2007
Automatic error detection and reduction for an odometric sensor based on two optical mice A Bonarini, M Matteucci, M Restelli Proceedings of the 2005 IEEE international conference on robotics and …, 2005	108	2005
Stochastic variance-reduced policy gradient M Papini, D Binaghi, G Canonaco, M Pirotta, M Restelli International Conference on Machine Learning, 4023-4032, 2018	98	2018
A multiobjective reinforcement learning approach to water resources systems operation: Pareto frontier approximation in a single run A Castelletti, F Pianosi, M Restelli Water Resources Research 49 (6), 3476-3486, 2013	89	2013
Data-driven dynamic emulation modelling for the optimal management of environmental systems A Castelletti, S Galelli, M Restelli, R Soncini-Sessa Environmental Modelling & Software 34, 30-43, 2012	88	2012
Safe Policy Iteration M Pirotta, M Restelli, A Pecorino, D Calandriello Proceedings of the 30th international conference on Machine learning, 307-315, 2013	87	2013
A kinematic-independent dead-reckoning sensor for indoor mobile robotics A Bonarini, M Matteucci, M Restelli 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2004	82	2004
Reinforcement distribution in fuzzy Q-learning A Bonarini, A Lazaric, F Montrone, M Restelli Fuzzy sets and systems 160 (10), 1420-1443, 2009	65	2009
Policy optimization via importance sampling AM Metelli, M Papini, F Faccio, M Restelli Advances in Neural Information Processing Systems 31, 2018	63	2018
Policy gradient in Lipschitz Markov Decision Processes M Pirotta, M Restelli, L Bascetta Machine Learning 100 (2), 255-283, 2015	63	2015
Adaptive step-size for policy gradient methods M Pirotta, M Restelli, L Bascetta Advances in Neural Information Processing Systems 26, 2013	63	2013
Coherent transport of quantum states by deep reinforcement learning R Porotti, D Tamascelli, M Restelli, E Prati Communications Physics 2 (1), 1-9, 2019	61	2019
Sparse multi-task reinforcement learning D Calandriello, A Lazaric, M Restelli Advances in neural information processing systems 27, 2014	58	2014
Transfer from multiple MDPs A Lazaric, M Restelli Advances in Neural Information Processing Systems 24, 1746-1754, 2011	54	2011
Multi-objective reinforcement learning with continuous pareto frontier approximation M Pirotta, S Parisi, M Restelli Twenty-Ninth AAAI Conference on Artificial Intelligence, 2928-2934, 2015	52	2015
Learning to cooperate in multi-agent social dilemmas EM de Cote, A Lazaric, M Restelli Proceedings of the fifth international joint conference on Autonomous agents …, 2006	48	2006
Sharing Knowledge in Multi-Task Deep Reinforcement Learning C D'Eramo, D Tateo, A Bonarini, M Restelli, J Peters International Conference on Learning Representations, 2020	47	2020
A combinatorial-bandit algorithm for the online joint bid/budget optimization of pay-per-click advertising campaigns A Nuara, F Trovo, N Gatti, M Restelli Thirty-Second AAAI Conference on Artificial Intelligence, 2018	44	2018

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