Mohammad Ghavamzadeh

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Yinlam ChowResearch Scientist, Google ResearchVerified email at google.com
Alessandro LazaricResearch Scientist, Facebook Artificial Intelligence ResearchVerified email at inria.fr
Shie MannorProfessor of Electrical Engineering @ Technion & Researcher @ Nvidia ResearchVerified email at technion.ac.il
Rémi MunosDeepMindVerified email at inria.fr
Sridhar MahadevanDirector, Data Science Lab, Adobe Research & Professor, University of Massachusetts, AmherstVerified email at cs.umass.edu
Branislav KvetonAmazonVerified email at amazon.com
Csaba SzepesvariDeepMind & University of AlbertaVerified email at cs.ualberta.ca
Georgios TheocharousAdobe ResearchVerified email at adobe.com
Amir-massoud FarahmandVector Institute, University of TorontoVerified email at vectorinstitute.ai
Marek PetrikUniversity of New HampshireVerified email at cs.unh.edu
Philip ThomasUniversity of Massachusetts AmherstVerified email at cs.umass.edu
Ofir NachumOpenAIVerified email at openai.com
Craig BoutilierPrincipal Scientist, GoogleVerified email at google.com
Shalabh BhatnagarProfessor in the Department of Computer Science and Automation, Indian Institute of ScienceVerified email at iisc.ac.in
Richard S. SuttonKeen, Amii, and University of AlbertaVerified email at richsutton.com
Hung BuiResearch Scientist, Google DeepMindVerified email at google.com
Zheng WenGoogle DeepMindVerified email at google.com
Aviv TamarTechnionVerified email at technion.ac.il
Bo LiuEx-Associate Professor, AAAI SM, IEEE SMVerified email at cs.umass.edu
Matthieu GeistGoogle DeepMind (on leave of Professor, Université de Lorraine)Verified email at univ-lorraine.fr

Mohammad Ghavamzadeh

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Reinforcement Learning Online Learning Machine Learning Control AI


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges M Abdar, F Pourpanah, S Hussain, D Rezazadegan, L Liu, ... Information Fusion, 2021	1331	2021
Natural Actor–critic Algorithms S Bhatnagar, RS Sutton, M Ghavamzadeh, M Lee Automatica 45 (11), 2471-2482, 2009	1013*	2009
Bayesian Reinforcement Learning: A Survey M Ghavamzadeh, S Mannor, J Pineau, A Tamar Foundations and Trends in Machine Learning 8 (5-6), 359-483, 2015	493	2015
A Lyapunov-based Approach to Safe Reinforcement Learning Y Chow, O Nachum, E Duenez-Guzman, M Ghavamzadeh Neural Information Processing Systems, 8103-8112, 2018	479	2018
Risk-constrained Reinforcement Learning with Percentile Risk Criteria Y Chow, M Ghavamzadeh, L Janson, M Pavone Journal of Machine Learning Research (JMLR) 18, 6070-6120, 2017	446	2017
Algorithms for CVaR Optimization in MDPs Y Chow, M Ghavamzadeh Advances in Neural Information Processing Systems, 3509-3517, 2014	350	2014
Best Arm Identification: A Unified Approach to Fixed Budget and Fixed Confidence V Gabillon, M Ghavamzadeh, A Lazaric Neural Information Processing Systems, 3221-3229, 2012	333	2012
High-confidence Off-policy Evaluation P Thomas, G Theocharous, M Ghavamzadeh AAAI, 3000-3006, 2015	285	2015
Actor-Critic Algorithms for Risk-sensitive MDPs LA Prashanth, M Ghavamzadeh Neural Information Processing Systems, 252-260, 2013	275*	2013
More Robust Doubly Robust Off-policy Evaluation M Farajtabar, Y Chow, M Ghavamzadeh ICML, 1447-1456, 2018	231	2018
Safe Policy Learning for Continuous Control Y Chow, O Nachum, A Faust, E Duenez-Guzman, M Ghavamzadeh Conference on Robot Learning (CoRL), 2020	217*	2020
High Confidence Policy Improvement P Thomas, G Theocharous, M Ghavamzadeh ICML, 2380-2388, 2015	203	2015
Supervised actor-critic reinforcement learning MT Rosenstein, AG Barto, J Si, A Barto, W Powell, D Wunsch Learning and Approximate Dynamic Programming: Scaling Up to the Real World …, 2004	192	2004
Speedy Q-learning M Ghavamzadeh, H Kappen, M Azar, R Munos Neural Information Processing Systems 24, 2411-2419, 2011	188*	2011
Hierarchical Multi-agent Reinforcement Learning R Makar, S Mahadevan, M Ghavamzadeh International Conference on Autonomous Agents, 246-253, 2001	188	2001
Personalized Ad Recommendation Systems for Life-time Value Optimization with Guarantees G Theocharous, PS Thomas, M Ghavamzadeh IJCAI, 1806-1812, 2015	183*	2015
Hierarchical Multi-agent Reinforcement Learning M Ghavamzadeh, S Mahadevan, R Makar Journal of Autonomous Agents and Multi-Agent Systems (JAAMAS) 13 (2), 197-229, 2006	168	2006
Benchmarking Batch Deep Reinforcement Learning Algorithms S Fujimoto, E Conti, M Ghavamzadeh, J Pineau arXiv preprint arXiv:1910.01708, 2019	167	2019
Finite-Sample Analysis of Proximal Gradient TD Algorithms B Liu, J Liu, M Ghavamzadeh, S Mahadevan, M Petrik UAI, 504-513, 2015	167*	2015
Regularized Policy Iteration AM Farahmand, M Ghavamzadeh, C Szepesvári, S Mannor Neural Information Processing Systems, 441-448, 2008	161	2008

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