Marcello Restelli

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Alberto Maria MetelliAssistant Professor, Politecnico di MilanoVerified email at polimi.it
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
Francesco TrovòPolitecnico di Milano, Dipartimento di Elettronica, Informazione e BioingegneriaVerified email at polimi.it
Nicola GattiPolitecnico di MilanoVerified email at elet.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 PapiniPolitecnico di MilanoVerified email at polimi.it
Andrea TirinzoniMetaVerified email at fb.com
Alessandro NuaraPhD student, Politecnico di MilanoVerified email at polimi.it
Mirco MuttiTechnionVerified email at technion.ac.il
Carlo D'EramoProfessor of Reinforcement Learning @ University of Würzburg | Group leader @ TU DarmstadtVerified email at uni-wuerzburg.de
Stefano GalelliAssociate Professor, Cornell UniversityVerified email at cornell.edu
Luca BascettaAssociate Professor, Department of Electronics Information and Bioengineering, Politecnico di MilanoVerified email at polimi.it
Lorenzo BisiAI Specialist, ML cubeVerified email at polimi.it
Edoardo Vittori, PhDIntesa SanpaoloVerified email at polimi.it
Amarildo LikmetaUniversita di Bologna, Politecnico di MilanoVerified email at unibo.it
Luca SabbioniPolitecnico di MilanoVerified email at polimi.it
Giorgia RamponiETH ZurichVerified email at inf.ethz.ch

Marcello Restelli

Associate Professor, Politecnico di Milano

Verified email at polimi.it - Homepage

Machine Learning Reinforcement Learning


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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	204	2008
Tree‐based reinforcement learning for optimal water reservoir operation A Castelletti, S Galelli, M Restelli, R Soncini‐Sessa Water Resources Research 46 (9), 2010	203	2010
Reinforcement learning in continuous action spaces through sequential Monte Carlo methods A Lazaric, M Restelli, A Bonarini In: Adv. Neural Information Proc. Systems, 2007	183	2007
Stochastic variance-reduced policy gradient M Papini, D Binaghi, G Canonaco, M Pirotta, M Restelli International Conference on Machine Learning, 4023-4032, 2018	166	2018
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), 26, 2022	161	2022
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	115	2013
Safe Policy Iteration M Pirotta, M Restelli, A Pecorino, D Calandriello Proceedings of the 30th international conference on Machine learning, 307-315, 2013	111	2013
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
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	99	2020
Policy optimization via importance sampling AM Metelli, M Papini, F Faccio, M Restelli Advances in Neural Information Processing Systems 31, 2018	95	2018
Policy gradient in Lipschitz Markov Decision Processes M Pirotta, M Restelli, L Bascetta Machine Learning 100 (2), 255-283, 2015	95	2015
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	94	2012
Adaptive step-size for policy gradient methods M Pirotta, M Restelli, L Bascetta Advances in Neural Information Processing Systems 26, 2013	82	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
Coherent transport of quantum states by deep reinforcement learning R Porotti, D Tamascelli, M Restelli, E Prati Communications Physics 2 (1), 61, 2019	81	2019
Sparse multi-task reinforcement learning D Calandriello, A Lazaric, M Restelli Advances in neural information processing systems 27, 2014	77	2014
Feature selection via mutual information: New theoretical insights M Beraha, AM Metelli, M Papini, A Tirinzoni, M Restelli 2019 international joint conference on neural networks (IJCNN), 1-9, 2019	74	2019
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	70	2015
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
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	64	2014

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