Aviv Tamar

Cited by

	All	Since 2016
Citations	3498	3411
h-index	25	24
i10-index	36	34

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20132014201520162017201820192020202114 17 33 83 190 523 1013 1548 38

Co-authors

Pieter AbbeelUC Berkeley | Covariant.AIVerified email at cs.berkeley.edu
Shie MannorProfessor of Electrical Engineering @ Technion & Researcher @ Nvidia ResearchVerified email at technion.ac.il
Yi WuIIIS, Tsinghua UniversityVerified email at mail.tsinghua.edu.cn
Michael SchapiraProfessor of Computer Science, The Hebrew University of JerusalemVerified email at huji.ac.il
Thanard KurutachPhD candidate, UC BerkeleyVerified email at berkeley.edu
Dotan Di CastroBosch Center for AI, Haifa, IsraelVerified email at bosch.com
Igor MordatchUC BerkeleyVerified email at berkeley.edu
Garrett ThomasStanford UniversityVerified email at stanford.edu
Yinlam ChowResearch Scientist, Google ResearchVerified email at google.com
Mohammad GhavamzadehGoogle ResearchVerified email at google.com
Ryan LoweOpenAIVerified email at openai.com
Jean HarbMcGill UniversityVerified email at mail.mcgill.ca
Sergey LevineUC Berkeley, GoogleVerified email at eecs.berkeley.edu
Stuart RussellProfessor of Computer Science, University of California, BerkeleyVerified email at cs.berkeley.edu
Asaf ValadarskyHebrew University of JerusalemVerified email at mail.huji.ac.il
Dafna ShahafAssistant Professor of Computer Science, The Hebrew University of JerusalemVerified email at cs.huji.ac.il
Yonatan GlassnerGeneral MotorsVerified email at gm.com
Joshua AchiamPhD Student, UC Berkeley; Research Scientist, OpenAI.Verified email at berkeley.edu
David HeldAssistant Professor in the Robotics Institute, Carnegie Mellon UniversityVerified email at andrew.cmu.edu
Marco PavoneAssociate Professor of Aeronautics and Astronautics, Stanford UniversityVerified email at stanford.edu

Aviv Tamar

Technion

Verified email at technion.ac.il - Homepage

Machine Learning Reinforcement Learning Artificial Intelligence


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Multi-agent actor-critic for mixed cooperative-competitive environments R Lowe, Y Wu, A Tamar, J Harb, P Abbeel, I Mordatch arXiv preprint arXiv:1706.02275, 2017	1049	2017
Value iteration networks A Tamar, Y Wu, G Thomas, S Levine, P Abbeel arXiv preprint arXiv:1602.02867, 2016	417	2016
Constrained policy optimization J Achiam, D Held, A Tamar, P Abbeel International Conference on Machine Learning, 22-31, 2017	328	2017
Bayesian reinforcement learning: A survey M Ghavamzadeh, S Mannor, J Pineau, A Tamar arXiv preprint arXiv:1609.04436, 2016	226	2016
Model-ensemble trust-region policy optimization T Kurutach, I Clavera, Y Duan, A Tamar, P Abbeel arXiv preprint arXiv:1802.10592, 2018	169	2018
Risk-sensitive and robust decision-making: a cvar optimization approach Y Chow, A Tamar, S Mannor, M Pavone arXiv preprint arXiv:1506.02188, 2015	119	2015
Policy gradients with variance related risk criteria D Di Castro, A Tamar, S Mannor arXiv preprint arXiv:1206.6404, 2012	115	2012
Policy gradients with variance related risk criteria D Di Castro, A Tamar, S Mannor arXiv preprint arXiv:1206.6404, 2012	115	2012
Learning plannable representations with causal infogan T Kurutach, A Tamar, G Yang, S Russell, P Abbeel arXiv preprint arXiv:1807.09341, 2018	82	2018
Optimizing the CVaR via sampling A Tamar, Y Glassner, S Mannor Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015	79	2015
Learning to route A Valadarsky, M Schapira, D Shahaf, A Tamar Proceedings of the 16th ACM workshop on hot topics in networks, 185-191, 2017	75	2017
Learning robotic assembly from cad G Thomas, M Chien, A Tamar, JA Ojea, P Abbeel 2018 IEEE International Conference on Robotics and Automation (ICRA), 3524-3531, 2018	67	2018
A deep reinforcement learning perspective on internet congestion control N Jay, N Rotman, B Godfrey, M Schapira, A Tamar International Conference on Machine Learning, 3050-3059, 2019	63	2019
Scaling up robust MDPs using function approximation A Tamar, S Mannor, H Xu International Conference on Machine Learning, 181-189, 2014	55	2014
Learning generalized reactive policies using deep neural networks E Groshev, M Goldstein, A Tamar, S Srivastava, P Abbeel Proceedings of the International Conference on Automated Planning and …, 2018	43	2018
Learning from the hindsight plan—episodic mpc improvement A Tamar, G Thomas, T Zhang, S Levine, P Abbeel 2017 IEEE International Conference on Robotics and Automation (ICRA), 336-343, 2017	40	2017
Reinforcement learning on variable impedance controller for high-precision robotic assembly J Luo, E Solowjow, C Wen, JA Ojea, AM Agogino, A Tamar, P Abbeel 2019 International Conference on Robotics and Automation (ICRA), 3080-3087, 2019	39	2019
Policy gradient for coherent risk measures A Tamar, Y Chow, M Ghavamzadeh, S Mannor arXiv preprint arXiv:1502.03919, 2015	37	2015
Generalized emphatic temporal difference learning: Bias-variance analysis A Hallak, A Tamar, R Munos, S Mannor Proceedings of the AAAI Conference on Artificial Intelligence 30 (1), 2016	34	2016
Learning the variance of the reward-to-go A Tamar, D Di Castro, S Mannor The Journal of Machine Learning Research 17 (1), 361-396, 2016	32	2016

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