Marcello Restelli

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Citations	3766	2824
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Andrea BonariniFull Professor, Politecnico di Milano, Dipartimento di Eletronica, Informazione e Biongegneria, AIVerified email at polimi.it
Matteo PirottaResearch Scientist, Meta (FAIR)Verified email at fb.com
Alessandro LazaricResearch Scientist, Facebook Artificial Intelligence ResearchVerified email at inria.fr
Alberto Maria MetelliPostdoctoral Researcher, Politecnico di MilanoVerified email at polimi.it
Nicola GattiPolitecnico di MilanoVerified email at elet.polimi.it
Francesco TrovòPolitecnico di Milano, Dipartimento di Elettronica, Informazione e BioingegneriaVerified email at polimi.it
Andrea CastellettiProfessor, Politecnico di MilanoVerified email at polimi.it
Matteo MatteucciFull Professor, Department of Electronics Information and Bioengineering, Politecnico di MilanoVerified email at polimi.it
Matteo PapiniUniversitat Pompeu FabraVerified email at polimi.it
Andrea TirinzoniMeta AIVerified 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'EramoProfessor of Reinforcement Learning @ University of Würzburg | Group leader @ hessian.AIVerified email at uni-wuerzburg.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
Lorenzo BisiPhD student, Politecnico di MilanoVerified email at polimi.it
Edoardo Vittori, PhDIntesa SanpaoloVerified email at polimi.it
Stefano PaladinoPolitecnico di MilanoVerified email at polimi.it
Giorgia RamponiETH ZurichVerified email at inf.ethz.ch
Amarildo LikmetaUniversita di Bologna, Politecnico di MilanoVerified email at unibo.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	187	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	182	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	160	2007
Stochastic variance-reduced policy gradient M Papini, D Binaghi, G Canonaco, M Pirotta, M Restelli International Conference on Machine Learning, 4023-4032, 2018	125	2018
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
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	99	2013
Safe Policy Iteration M Pirotta, M Restelli, A Pecorino, D Calandriello Proceedings of the 30th international conference on Machine learning, 307-315, 2013	99	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	90	2012
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	81	2004
Policy optimization via importance sampling AM Metelli, M Papini, F Faccio, M Restelli Advances in Neural Information Processing Systems 31, 2018	74	2018
Policy gradient in Lipschitz Markov Decision Processes M Pirotta, M Restelli, L Bascetta Machine Learning 100 (2), 255-283, 2015	73	2015
Adaptive step-size for policy gradient methods M Pirotta, M Restelli, L Bascetta Advances in Neural Information Processing Systems 26, 2013	71	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	69	2019
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	66	2020
Reinforcement distribution in fuzzy Q-learning A Bonarini, A Lazaric, F Montrone, M Restelli Fuzzy sets and systems 160 (10), 1420-1443, 2009	66	2009
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	62	2015
Sparse multi-task reinforcement learning D Calandriello, A Lazaric, M Restelli Advances in neural information processing systems 27, 2014	62	2014
Transfer from multiple MDPs A Lazaric, M Restelli Advances in Neural Information Processing Systems 24, 1746-1754, 2011	60	2011
A practical guide to multi-objective reinforcement learning and planning CF Hayes, R Rădulescu, E Bargiacchi, J Källström, M Macfarlane, ... Autonomous Agents and Multi-Agent Systems 36 (1), 1-59, 2022	54	2022
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	53	2014

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