Amir-massoud Farahmand

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Csaba SzepesvariDeepMind & University of AlbertaVerified email at cs.ualberta.ca
Mohammad GhavamzadehGoogle ResearchVerified email at google.com
Daniel NikovskiGroup Manager, Mitsubishi Electric Research LabsVerified email at merl.com
Shie MannorProfessor of Electrical Engineering @ Technion & Researcher @ Nvidia ResearchVerified email at technion.ac.il
Doina PrecupDeepMind and McGill UniversityVerified email at cs.mcgill.ca
Azad ShademanIntuitive Surgical Inc.Verified email at intusurg.com
Martin JagersandUniversity of AlbertaVerified email at cs.ualberta.ca
Andre BarretoResearch Scientist, Google DeepMindVerified email at google.com
Majid Nili AhmadabadiProfessor of ECE, University of TehranVerified email at ut.ac.ir
Joelle PineauSchool of Computer Science, McGill University; FAIR, Meta AI; MilaVerified email at cs.mcgill.ca
Yangchen PanUniversity of OxfordVerified email at eng.ox.ac.uk
Babak N AraabiProfessor of ECE, University of TehranVerified email at ut.ac.ir
Saleh NabiPrincipal Research Scientist, Mitsubishi Electric Research LaboratoriesVerified email at merl.com
Martha WhiteUniversity of AlbertaVerified email at ualberta.ca
J. Andrew BagnellCarnegie Mellon UniversityVerified email at ri.cmu.edu
Beomjoon KimKorea Advanced Institute of Science & Technology (KAIST)Verified email at kaist.ac.kr
mouhacine benosmanMERL- Data Analytics GroupVerified email at merl.com
Rémi MunosDeepMindVerified email at inria.fr
De-An HuangStanford UniversityVerified email at cs.stanford.edu
Kris KitaniCarnegie Mellon University, Robotics InstituteVerified email at cs.cmu.edu

Amir-massoud Farahmand

Vector Institute, University of Toronto

Verified email at vectorinstitute.ai - Homepage

Machine Learning Reinforcement Learning Sequential Decision Making Statistical Learning Theory


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Error propagation for approximate policy and value iteration A Farahmand, C Szepesvári, R Munos Advances in Neural Information Processing Systems (NeurIPS), 568-576, 2010	210	2010
Regularized Policy Iteration A Farahmand, M Ghavamzadeh, S Mannor, C Szepesvári Advances in Neural Information Processing Systems 21 (NeurIPS 2008), 441-448, 2009	159	2009
Learning from Limited Demonstrations B Kim, A Farahmand, J Pineau, D Precup Advances in Neural Information Processing Systems (NeurIPS), 2859-2867, 2013	117	2013
Manifold-adaptive dimension estimation A Farahmand, C Szepesvári, JY Audibert Proceedings of the 24th International Conference on Machine Learning (ICML …, 2007	112	2007
Regularized policy iteration with nonparametric function spaces A Farahmand, M Ghavamzadeh, C Szepesvári, S Mannor Journal of Machine Learning Research (JMLR) 17 (1), 4809-4874, 2016	96	2016
Regularized fitted Q-iteration for planning in continuous-space Markovian decision problems A Farahmand, M Ghavamzadeh, C Szepesvári, S Mannor American Control Conference (ACC), 725-730, 2009	90*	2009
Value-aware loss function for model-based reinforcement learning A Farahmand, A Barreto, D Nikovski Artificial Intelligence and Statistics (AISTATS), 1486-1494, 2017	85	2017
Robust jacobian estimation for uncalibrated visual servoing A Shademan, A Farahmand, M Jägersand IEEE International Conference on Robotics and Automation (ICRA), 5564-5569, 2010	74	2010
Model Selection in Reinforcement Learning AM Farahmand, C Szepesvári Machine learning 85 (3), 299-332, 2011	60	2011
Action-Gap Phenomenon in Reinforcement Learning AM Farahmand Neural Information Processing Systems (NeurIPS), 2011	55	2011
Global visual-motor estimation for uncalibrated visual servoing A Farahmand, A Shademan, M Jagersand IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS …, 2007	55*	2007
Iterative Value-Aware Model Learning A Farahmand Advances in Neural Information Processing Systems (NeurIPS), 9072-9083, 2018	45	2018
Regularization in Reinforcement Learning AM Farahmand Department of Computing Science, University of Alberta, 2011	39	2011
Deep reinforcement learning for partial differential equation control A Farahmand, S Nabi, DN Nikovski American Control Conference (ACC), 3120-3127, 2017	38	2017
Model-based and model-free reinforcement learning for visual servoing A Farahmand, A Shademan, M Jagersand, C Szepesvári IEEE International Conference on Robotics and Automation (ICRA), 2917-2924, 2009	36*	2009
Attentional network for visual object detection K Hara, MY Liu, O Tuzel, A Farahmand arXiv preprint arXiv:1702.01478, 2017	34	2017
Approximate MaxEnt Inverse Optimal Control and its Application for Mental Simulation of Human Interactions DA Huang, AM Farahmand, KM Kitani, JA Bagnell AAAI Conference on Artificial Intelligence (AAAI), 2015	31	2015
Interaction of Culture-based Learning and Cooperative Co-evolution and its Application to Automatic Behavior-based System Design AM Farahmand, MN Ahmadabadi, C Lucas, BN Araabi IEEE Transactions on Evolutionary Computation 14 (1), 23-57, 2010	24	2010
Regularized fitted Q-iteration: Application to planning AM Farahmand, M Ghavamzadeh, C Szepesvári, S Mannor Recent Advances in Reinforcement Learning, 55-68, 2008	24	2008
Object Detection System and Object Detection Method MY Liu, O Tuzel, A Farahmand, K Hara US Patent App. 15/218,182, 2018	20	2018

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