Aviv Tamar - Google Scholar

Cited by

	All	Since 2015
Citations	2682	2635
h-index	21	21
i10-index	32	31

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2013201420152016201720182019202014 17 28 83 190 509 1052 751

Co-authors

Pieter AbbeelUC Berkeley | Covariant.AIVerified email at cs.berkeley.edu
Shie MannorProfessor of Electrical Engineering, TechnionVerified email at technion.ac.il
Yi WuResearcher, OpenAI Inc.Verified email at cs.berkeley.edu
Thanard KurutachPhD student, 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
Michael SchapiraProfessor of Computer Science, The Hebrew University of JerusalemVerified email at huji.ac.il
Mohammad GhavamzadehGoogle ResearchVerified email at inria.fr
Sergey LevineUC Berkeley, GoogleVerified email at eecs.berkeley.edu
Ryan LoweOpenAIVerified email at openai.com
Jean HarbMcGill UniversityVerified email at mail.mcgill.ca
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, YI Wu, A Tamar, J Harb, OAIP Abbeel, I Mordatch Advances in neural information processing systems, 6379-6390, 2017	785	2017
Value iteration networks A Tamar, Y Wu, G Thomas, S Levine, P Abbeel Advances in Neural Information Processing Systems, 2154-2162, 2016	360	2016
Constrained policy optimization J Achiam, D Held, A Tamar, P Abbeel arXiv preprint arXiv:1705.10528, 2017	251	2017
Bayesian reinforcement learning: A survey M Ghavamzadeh, S Mannor, J Pineau, A Tamar arXiv preprint arXiv:1609.04436, 2016	196	2016
Model-ensemble trust-region policy optimization T Kurutach, I Clavera, Y Duan, A Tamar, P Abbeel arXiv preprint arXiv:1802.10592, 2018	132	2018
Policy gradients with variance related risk criteria D Di Castro, A Tamar, S Mannor arXiv preprint arXiv:1206.6404, 2012	94	2012
Policy gradients with variance related risk criteria D Di Castro, A Tamar, S Mannor arXiv preprint arXiv:1206.6404, 2012	94	2012
Risk-sensitive and robust decision-making: a cvar optimization approach Y Chow, A Tamar, S Mannor, M Pavone Advances in Neural Information Processing Systems, 1522-1530, 2015	93	2015
Optimizing the CVaR via sampling A Tamar, Y Glassner, S Mannor Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015	66	2015
Learning plannable representations with causal infogan T Kurutach, A Tamar, G Yang, SJ Russell, P Abbeel Advances in Neural Information Processing Systems, 8733-8744, 2018	57	2018
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	54	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), 1-9, 2018	47	2018
Scaling up robust MDPs using function approximation A Tamar, S Mannor, H Xu International Conference on Machine Learning, 181-189, 2014	43	2014
Learning generalized reactive policies using deep neural networks E Groshev, A Tamar, M Goldstein, S Srivastava, P Abbeel 2018 AAAI Spring Symposium Series, 2018	36	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	35	2019
Policy gradient for coherent risk measures A Tamar, Y Chow, M Ghavamzadeh, S Mannor Advances in Neural Information Processing Systems, 1468-1476, 2015	30	2015
Temporal difference methods for the variance of the reward to go A Tamar, D Di Castro, S Mannor International Conference on Machine Learning, 495-503, 2013	30	2013
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	29	2017
Generalized emphatic temporal difference learning: Bias-variance analysis A Hallak, A Tamar, R Munos, S Mannor Thirtieth AAAI Conference on Artificial Intelligence, 2016	28	2016
Shallow updates for deep reinforcement learning N Levine, T Zahavy, DJ Mankowitz, A Tamar, S Mannor Advances in Neural Information Processing Systems, 3135-3145, 2017	27	2017

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