Aviv Tamar

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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 WuInstitute for Interdisciplinary Information Sciences, Tsinghua UniversityVerified email at mail.tsinghua.edu.cn
Michael SchapiraProfessor of Computer Science, The Hebrew University of JerusalemVerified email at huji.ac.il
Thanard KurutachResearch Scientist, Cruise llcVerified email at berkeley.edu
Igor MordatchUC BerkeleyVerified email at berkeley.edu
Dotan Di CastroBosch Center for AI, Haifa, IsraelVerified email at bosch.com
Yinlam ChowResearch Scientist, Google ResearchVerified email at google.com
Garrett ThomasStanford UniversityVerified email at stanford.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
Sergey LevineUC Berkeley, GoogleVerified email at eecs.berkeley.edu
Noga H. RotmanHebrew University of JerusalemVerified email at cs.huji.ac.il
Asaf ValadarskyHebrew University of JerusalemVerified email at mail.huji.ac.il
Dafna ShahafAssociate Professor of Computer Science, The Hebrew University of JerusalemVerified email at cs.huji.ac.il
Joshua AchiamResearch Scientist, OpenAIVerified email at berkeley.edu
David HeldAssistant Professor in the Robotics Institute, Carnegie Mellon UniversityVerified email at andrew.cmu.edu
Yonatan GlassnerGeneral MotorsVerified email at gm.com
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, OAI Pieter Abbeel, I Mordatch Advances in neural information processing systems 30, 2017	2153	2017
Constrained policy optimization J Achiam, D Held, A Tamar, P Abbeel International conference on machine learning, 22-31, 2017	649	2017
Value iteration networks A Tamar, Y Wu, G Thomas, S Levine, P Abbeel Advances in neural information processing systems 29, 2016	556	2016
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	327	2015
Model-ensemble trust-region policy optimization T Kurutach, I Clavera, Y Duan, A Tamar, P Abbeel arXiv preprint arXiv:1802.10592, 2018	315	2018
Risk-sensitive and robust decision-making: a cvar optimization approach Y Chow, A Tamar, S Mannor, M Pavone Advances in neural information processing systems 28, 2015	208	2015
Policy gradients with variance related risk criteria D Di Castro, A Tamar, S Mannor arXiv preprint arXiv:1206.6404, 2012	163	2012
Policy gradients with variance related risk criteria D Di Castro, A Tamar, S Mannor arXiv preprint arXiv:1206.6404, 2012	163	2012
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	158	2019
Learning plannable representations with causal infogan T Kurutach, A Tamar, G Yang, SJ Russell, P Abbeel Advances in Neural Information Processing Systems 31, 2018	135	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	131	2017
Optimizing the CVaR via sampling A Tamar, Y Glassner, S Mannor Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015	124	2015
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	114	2018
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	92	2019
Scaling up robust MDPs using function approximation A Tamar, S Mannor, H Xu International conference on machine learning, 181-189, 2014	89	2014
Policy gradient for coherent risk measures A Tamar, Y Chow, M Ghavamzadeh, S Mannor Advances in neural information processing systems 28, 2015	81	2015
Learning generalized reactive policies using deep neural networks E Groshev, A Tamar, M Goldstein, S Srivastava, P Abbeel 2018 AAAI Spring Symposium Series, 2018	77	2018
Learning robotic manipulation through visual planning and acting A Wang, T Kurutach, K Liu, P Abbeel, A Tamar arXiv preprint arXiv:1905.04411, 2019	69	2019
Bayesian relational memory for semantic visual navigation Y Wu, Y Wu, A Tamar, S Russell, G Gkioxari, Y Tian Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019	61	2019
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	57	2016

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