Marcello Restelli

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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
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
Andrea CastellettiProfessor, Politecnico di MilanoVerified email at polimi.it
Francesco TrovòPolitecnico di MilanoVerified email at polimi.it
Alberto Maria MetelliPostdoctoral Researcher, Politecnico di MilanoVerified email at polimi.it
Matteo PapiniPolitecnico di MilanoVerified email at polimi.it
Stefano GalelliAssociate Professor, Singapore University of Technology and DesignVerified email at sutd.edu.sg
Alessandro NuaraPhD student, Politecnico di MilanoVerified email at polimi.it
Andrea TirinzoniInria LilleVerified email at inria.fr
Luca BascettaAssociate Professor, Department of Electronics Information and Bioengineering, Politecnico di MilanoVerified email at polimi.it
Carlo D'EramoPostdoctoral researcher @ Technische Universität DarmstadtVerified email at robot-learning.de
Stefano PaladinoPolitecnico di MilanoVerified email at polimi.it
Daniele CalandrielloResearch Scientist, DeepMindVerified email at google.com
Enrique Munoz de CoteProfessor of Computer Science at INAOE; CSO @ People & AI; past: Director at SecondmindVerified email at people-ai.com
Domenico Giorgio SorrentiUniversità degli Studi di Milano - BicoccaVerified email at unimib.it
Simone ParisiFacebook AI ResearchVerified email at fb.com
Mirco MuttiPolitecnico 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	160	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	145	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	129	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	107	2005
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	81	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
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	80	2013
Safe Policy Iteration M Pirotta, M Restelli, A Pecorino, D Calandriello Proceedings of the 30th international conference on Machine learning, 307-315, 2013	63	2013
Reinforcement distribution in fuzzy Q-learning A Bonarini, A Lazaric, F Montrone, M Restelli Fuzzy sets and systems 160 (10), 1420-1443, 2009	62	2009
Stochastic variance-reduced policy gradient M Papini, D Binaghi, G Canonaco, M Pirotta, M Restelli International Conference on Machine Learning, 4023-4032, 2018	59	2018
Adaptive step-size for policy gradient methods M Pirotta, M Restelli, L Bascetta Advances in Neural Information Processing Systems 26, 1394-1402, 2013	56	2013
Policy gradient in Lipschitz Markov Decision Processes M Pirotta, M Restelli, L Bascetta Machine Learning 100 (2), 255-283, 2015	48	2015
Transfer from multiple MDPs A Lazaric, M Restelli Advances in Neural Information Processing Systems 24, 1746-1754, 2011	47	2011
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	47	2006
Sparse multi-task reinforcement learning D Calandriello, A Lazaric, M Restelli	46	2014
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	44	2015
Policy optimization via importance sampling AM Metelli, M Papini, F Faccio, M Restelli arXiv preprint arXiv:1809.06098, 2018	42	2018
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	38	2014
Self-development framework for reinforcement learning agents A Bonarini, A Lazaric, M Restelli, P Vitali Proceedings of the Fifth International Conference on Development and …, 2006	33	2006
Coherent transport of quantum states by deep reinforcement learning R Porotti, D Tamascelli, M Restelli, E Prati Communications Physics 2 (1), 1-9, 2019	32	2019

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