Aviv Tamar - RankMe

143 papers A* 41B 1C 1Misc 7Journal 80Unranked 13

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Hierarchical Entity-centric Reinforcement Learning with Factored Subgoal Diffusion. CoRR Dan Haramati, Carl Qi, Tal Daniel, Amy Zhang, Aviv Tamar, George Konidaris
2026	J	`jnl`	Latent Particle World Models: Self-supervised Object-centric Stochastic Dynamics Modeling. CoRR Tal Daniel, Carl Qi, Dan Haramati, Amir Zadeh, Chuan Li, Aviv Tamar, Deepak Pathak, David Held
2025	A*	`conf`	A Classification View on Meta Learning Bandits. ICML Mirco Mutti, Jeongyeol Kwon, Shie Mannor, Aviv Tamar
2025	J	`jnl`	A Classification View on Meta Learning Bandits. CoRR Mirco Mutti, Jeongyeol Kwon, Shie Mannor, Aviv Tamar
2025	J	`jnl`	Blindfolded Experts Generalize Better: Insights from Robotic Manipulation and Videogames. CoRR Ev Zisselman, Mirco Mutti, Shelly Francis-Meretzki, Elisei Shafer, Aviv Tamar
2025	A*	`conf`	EC-Diffuser: Multi-Object Manipulation via Entity-Centric Behavior Generation. ICLR Carl Qi, Dan Haramati, Tal Daniel, Aviv Tamar, Amy Zhang
2025	A*	`conf`	From Configuration-Space Clearance to Feature-Space Margin: Sample Complexity in Learning-Based Collision Detection. ICRA Sapir Tubul, Aviv Tamar, Kiril Solovey, Oren Salzman
2025	J	`jnl`	From Configuration-Space Clearance to Feature-Space Margin: Sample Complexity in Learning-Based Collision Detection. CoRR Sapir Tubul, Aviv Tamar, Kiril Solovey, Oren Salzman
2025	J	`jnl`	MAD-DAG: Protecting Blockchain Consensus from MEV. CoRR Roi Bar Zur, Aviv Tamar, Ittay Eyal
2025	J	`jnl`	Toward Artificial Palpation: Representation Learning of Touch on Soft Bodies. CoRR Zohar Rimon, Elisei Shafer, Tal Tepper, Efrat Shimron, Aviv Tamar
2024	A*	`conf`	A Bayesian Approach to Online Planning. ICML Nir Greshler, David Ben-Eli, Carmel Rabinovitz, Gabi Guetta, Liran Gispan, Guy Zohar, Aviv Tamar
2024	J	`jnl`	A Bayesian Approach to Online Planning. CoRR Nir Greshler, David Ben-Eli, Carmel Rabinovitz, Gabi Guetta, Liran Gispan, Guy Zohar, Aviv Tamar
2024	J	`jnl`	DDLP: Unsupervised Object-centric Video Prediction with Deep Dynamic Latent Particles. Trans. Mach. Learn. Res. Tal Daniel, Aviv Tamar
2024	J	`jnl`	EC-Diffuser: Multi-Object Manipulation via Entity-Centric Behavior Generation. CoRR Carl Qi, Dan Haramati, Tal Daniel, Aviv Tamar, Amy Zhang
2024	A*	`conf`	Entity-Centric Reinforcement Learning for Object Manipulation from Pixels. ICLR Dan Haramati, Tal Daniel, Aviv Tamar
2024	J	`jnl`	Entity-Centric Reinforcement Learning for Object Manipulation from Pixels. CoRR Dan Haramati, Tal Daniel, Aviv Tamar
2024	A*	`conf`	MAMBA: an Effective World Model Approach for Meta-Reinforcement Learning. ICLR Zohar Rimon, Tom Jurgenson, Orr Krupnik, Gilad Adler, Aviv Tamar
2024	J	`jnl`	MAMBA: an Effective World Model Approach for Meta-Reinforcement Learning. CoRR Zohar Rimon, Tom Jurgenson, Orr Krupnik, Gilad Adler, Aviv Tamar
2024	J	`jnl`	RoboArm-NMP: a Learning Environment for Neural Motion Planning. CoRR Tom Jurgenson, Matan Sudry, Gal Avineri, Aviv Tamar
2024	A*	`conf`	Test-Time Regret Minimization in Meta Reinforcement Learning. ICML Mirco Mutti, Aviv Tamar
2024	J	`jnl`	Test-Time Regret Minimization in Meta Reinforcement Learning. CoRR Mirco Mutti, Aviv Tamar
2023	J	`jnl`	A Deep Learning Perspective on Network Routing. CoRR Yarin Perry, Felipe Vieira Frujeri, Chaim Hoch, Srikanth Kandula, Ishai Menache, Michael Schapira, Aviv Tamar
2023	A*	`conf`	ContraBAR: Contrastive Bayes-Adaptive Deep RL. ICML Era Choshen, Aviv Tamar
2023	J	`jnl`	ContraBAR: Contrastive Bayes-Adaptive Deep RL. CoRR Era Choshen, Aviv Tamar
2023	J	`jnl`	DDLP: Unsupervised Object-Centric Video Prediction with Deep Dynamic Latent Particles. CoRR Tal Daniel, Aviv Tamar
2023	Misc	`conf`	DOTE: Rethinking (Predictive) WAN Traffic Engineering. NSDI Yarin Perry, Felipe Vieira Frujeri, Chaim Hoch, Srikanth Kandula, Ishai Menache, Michael Schapira, Aviv Tamar
2023	—	`conf`	Deep Bribe: Predicting the Rise of Bribery in Blockchain Mining with Deep RL. SP (Workshops) Roi Bar Zur, Danielle Dori, Sharon Vardi, Ittay Eyal, Aviv Tamar
2023	J	`jnl`	Deep Bribe: Predicting the Rise of Bribery in Blockchain Mining with Deep RL. IACR Cryptol. ePrint Arch. Roi Bar Zur, Danielle Dori, Sharon Vardi, Ittay Eyal, Aviv Tamar
2023	A*	`conf`	Explore to Generalize in Zero-Shot RL. NeurIPS Ev Zisselman, Itai Lavie, Daniel Soudry, Aviv Tamar
2023	J	`jnl`	Explore to Generalize in Zero-Shot RL. CoRR Ev Zisselman, Itai Lavie, Daniel Soudry, Aviv Tamar
2023	Misc	`conf`	Fine-Tuning Generative Models as an Inference Method for Robotic Tasks. CoRL Orr Krupnik, Elisei Shafer, Tom Jurgenson, Aviv Tamar
2023	J	`jnl`	Fine-Tuning Generative Models as an Inference Method for Robotic Tasks. CoRR Orr Krupnik, Elisei Shafer, Tom Jurgenson, Aviv Tamar
2023	J	`jnl`	Goal-Conditioned Supervised Learning with Sub-Goal Prediction. CoRR Tom Jurgenson, Aviv Tamar
2023	Misc	`conf`	Hierarchical Planning for Rope Manipulation using Knot Theory and a Learned Inverse Model. CoRL Matan Sudry, Tom Jurgenson, Aviv Tamar, Erez Karpas
2023	A*	`conf`	Learning Control by Iterative Inversion. ICML Gal Leibovich, Guy Jacob, Or Avner, Gal Novik, Aviv Tamar
2023	A*	`conf`	Online Tool Selection with Learned Grasp Prediction Models. ICRA Khashayar Rohanimanesh, Jake Metzger, William Richards, Aviv Tamar
2023	J	`jnl`	Online Tool Selection with Learned Grasp Prediction Models. CoRR Khashayar Rohanimanesh, Jake Metzger, William Richards, Aviv Tamar
2023	A*	`conf`	TGRL: An Algorithm for Teacher Guided Reinforcement Learning. ICML Idan Shenfeld, Zhang-Wei Hong, Aviv Tamar, Pulkit Agrawal
2023	J	`jnl`	TGRL: An Algorithm for Teacher Guided Reinforcement Learning. CoRR Idan Shenfeld, Zhang-Wei Hong, Aviv Tamar, Pulkit Agrawal
2023	J	`jnl`	Towards Deployable RL - What's Broken with RL Research and a Potential Fix. CoRR Shie Mannor, Aviv Tamar
2023	A*	`conf`	WeRLman: To Tackle Whale (Transactions), Go Deep (RL). SP Roi Bar Zur, Ameer Abu-Hanna, Ittay Eyal, Aviv Tamar
2022	J	`jnl`	Learning Control by Iterative Inversion. CoRR Gal Leibovich, Guy Jacob, Or Avner, Gal Novik, Aviv Tamar
2022	A*	`conf`	Meta Reinforcement Learning with Finite Training Tasks - a Density Estimation Approach. NeurIPS Zohar Rimon, Aviv Tamar, Gilad Adler
2022	J	`jnl`	Meta Reinforcement Learning with Finite Training Tasks - a Density Estimation Approach. CoRR Zohar Rimon, Aviv Tamar, Gilad Adler
2022	A*	`conf`	Regularization Guarantees Generalization in Bayesian Reinforcement Learning through Algorithmic Stability. AAAI Aviv Tamar, Daniel Soudry, Ev Zisselman
2022	A*	`conf`	Unsupervised Image Representation Learning with Deep Latent Particles. ICML Tal Daniel, Aviv Tamar
2022	J	`jnl`	Unsupervised Image Representation Learning with Deep Latent Particles. CoRR Tal Daniel, Aviv Tamar
2022	A*	`conf`	Validate on Sim, Detect on Real - Model Selection for Domain Randomization. ICRA Gal Leibovich, Guy Jacob, Shadi Endrawis, Gal Novik, Aviv Tamar
2022	J	`jnl`	WeRLman: To Tackle Whale (Transactions), Go Deep (RL). IACR Cryptol. ePrint Arch. Roi Bar Zur, Ameer Abu-Hanna, Ittay Eyal, Aviv Tamar
2022	Misc	`conf`	WeRLman: to tackle whale (transactions), go deep (RL). SYSTOR Roi Bar Zur, Ameer Abu-Hanna, Ittay Eyal, Aviv Tamar
2021	A*	`conf`	Efficient Self-Supervised Data Collection for Offline Robot Learning. ICRA Shadi Endrawis, Gal Leibovich, Guy Jacob, Gal Novik, Aviv Tamar
2021	J	`jnl`	Efficient Self-Supervised Data Collection for Offline Robot Learning. CoRR Shadi Endrawis, Gal Leibovich, Guy Jacob, Gal Novik, Aviv Tamar
2021	A*	`conf`	Offline Meta Reinforcement Learning - Identifiability Challenges and Effective Data Collection Strategies. NeurIPS Ron Dorfman, Idan Shenfeld, Aviv Tamar
2021	J	`jnl`	Regularization Guarantees Generalization in Bayesian Reinforcement Learning through Algorithmic Stability. CoRR Aviv Tamar, Daniel Soudry, Ev Zisselman
2021	A*	`conf`	Soft-IntroVAE: Analyzing and Improving the Introspective Variational Autoencoder. CVPR Tal Daniel, Aviv Tamar
2021	A*	`conf`	Unsupervised Feature Learning for Manipulation with Contrastive Domain Randomization. ICRA Carmel Rabinovitz, Niko A. Grupen, Aviv Tamar
2021	J	`jnl`	Unsupervised Feature Learning for Manipulation with Contrastive Domain Randomization. CoRR Carmel Rabinovitz, Niko A. Grupen, Aviv Tamar
2021	J	`jnl`	Validate on Sim, Detect on Real - Model Selection for Domain Randomization. CoRR Gal Leibovich, Guy Jacob, Shadi Endrawis, Gal Novik, Aviv Tamar
2020	A*	`conf`	Constrained Policy Improvement for Efficient Reinforcement Learning. IJCAI Elad Sarafian, Aviv Tamar, Sarit Kraus
2020	J	`jnl`	Deep Residual Flow for Novelty Detection. CoRR Ev Zisselman, Aviv Tamar
2020	A*	`conf`	Deep Residual Flow for Out of Distribution Detection. CVPR Ev Zisselman, Aviv Tamar
2020	B	`conf`	Efficient MDP Analysis for Selfish-Mining in Blockchains. AFT Roi Bar Zur, Ittay Eyal, Aviv Tamar
2020	J	`jnl`	Efficient MDP Analysis for Selfish-Mining in Blockchains. CoRR Roi Bar Zur, Ittay Eyal, Aviv Tamar
2020	A*	`conf`	Hallucinative Topological Memory for Zero-Shot Visual Planning. ICML Kara Liu, Thanard Kurutach, Christine Tung, Pieter Abbeel, Aviv Tamar
2020	J	`jnl`	Hallucinative Topological Memory for Zero-Shot Visual Planning. CoRR Kara Liu, Thanard Kurutach, Christine Tung, Pieter Abbeel, Aviv Tamar
2020	J	`jnl`	Offline Meta Reinforcement Learning. CoRR Ron Dorfman, Aviv Tamar
2020	J	`jnl`	Online Safety Assurance for Deep Reinforcement Learning. CoRR Noga H. Rotman, Michael Schapira, Aviv Tamar
2020	Misc	`conf`	Online Safety Assurance for Learning-Augmented Systems. HotNets Noga H. Rotman, Michael Schapira, Aviv Tamar
2020	J	`jnl`	Robust 2D Assembly Sequencing via Geometric Planning with Learned Scores. CoRR Tzvika Geft, Aviv Tamar, Ken Goldberg, Dan Halperin
2020	J	`jnl`	Soft-IntroVAE: Analyzing and Improving the Introspective Variational Autoencoder. CoRR Tal Daniel, Aviv Tamar
2020	J	`jnl`	Sub-Goal Trees - a Framework for Goal-Based Reinforcement Learning. CoRR Tom Jurgenson, Or Avner, Edward Groshev, Aviv Tamar
2020	A*	`conf`	Sub-Goal Trees a Framework for Goal-Based Reinforcement Learning. ICML Tom Jurgenson, Or Avner, Edward Groshev, Aviv Tamar
2019	A*	`conf`	A Deep Reinforcement Learning Perspective on Internet Congestion Control. ICML Nathan Jay, Noga H. Rotman, Brighten Godfrey, Michael Schapira, Aviv Tamar
2019	C	`conf`	A Risk-Sensitive Finite-Time Reachability Approach for Safety of Stochastic Dynamic Systems. ACC Margaret P. Chapman, Jonathan Lacotte, Aviv Tamar, Donggun Lee, Kevin M. Smith, Victoria Cheng, Jaime F. Fisac, Susmit Jha, Marco Pavone, Claire J. Tomlin
2019	J	`jnl`	A Risk-Sensitive Finite-Time Reachability Approach for Safety of Stochastic Dynamic Systems. CoRR Margaret P. Chapman, Jonathan Lacotte, Aviv Tamar, Donggun Lee, Kevin M. Smith, Victoria Cheng, Jaime F. Fisac, Susmit Jha, Marco Pavone, Claire J. Tomlin
2019	A*	`conf`	Bayesian Relational Memory for Semantic Visual Navigation. ICCV Yi Wu, Yuxin Wu, Aviv Tamar, Stuart Russell, Georgia Gkioxari, Yuandong Tian
2019	J	`jnl`	Bayesian Relational Memory for Semantic Visual Navigation. CoRR Yi Wu, Yuxin Wu, Aviv Tamar, Stuart Russell, Georgia Gkioxari, Yuandong Tian
2019	J	`jnl`	Deep Variational Semi-Supervised Novelty Detection. CoRR Tal Daniel, Thanard Kurutach, Aviv Tamar
2019	A*	`conf`	Distributional Multivariate Policy Evaluation and Exploration with the Bellman GAN. ICML Dror Freirich, Tzahi Shimkin, Ron Meir, Aviv Tamar
2019	A*	`conf`	Domain Randomization for Active Pose Estimation. ICRA Xinyi Ren, Jianlan Luo, Eugen Solowjow, Juan Aparicio Ojea, Abhishek Gupta, Aviv Tamar, Pieter Abbeel
2019	J	`jnl`	Domain Randomization for Active Pose Estimation. CoRR Xinyi Ren, Jianlan Luo, Eugen Solowjow, Juan Aparicio Ojea, Abhishek Gupta, Aviv Tamar, Pieter Abbeel
2019	—	`conf`	Harnessing Reinforcement Learning for Neural Motion Planning. Robotics: Science and Systems Tom Jurgenson, Aviv Tamar
2019	J	`jnl`	Harnessing Reinforcement Learning for Neural Motion Planning. CoRR Tom Jurgenson, Aviv Tamar
2019	—	`conf`	Learning Robotic Manipulation through Visual Planning and Acting. Robotics: Science and Systems Angelina Wang, Thanard Kurutach, Pieter Abbeel, Aviv Tamar
2019	J	`jnl`	Learning Robotic Manipulation through Visual Planning and Acting. CoRR Angelina Wang, Thanard Kurutach, Kara Liu, Pieter Abbeel, Aviv Tamar
2019	J	`jnl`	Multi Agent Reinforcement Learning with Multi-Step Generative Models. CoRR Orr Krupnik, Igor Mordatch, Aviv Tamar
2019	Misc	`conf`	Multi-Agent Reinforcement Learning with Multi-Step Generative Models. CoRL Orr Krupnik, Igor Mordatch, Aviv Tamar
2019	A*	`conf`	Reinforcement Learning on Variable Impedance Controller for High-Precision Robotic Assembly. ICRA Jianlan Luo, Eugen Solowjow, Chengtao Wen, Juan Aparicio Ojea, Alice M. Agogino, Aviv Tamar, Pieter Abbeel
2019	J	`jnl`	Reinforcement Learning on Variable Impedance Controller for High-Precision Robotic Assembly. CoRR Jianlan Luo, Eugen Solowjow, Chengtao Wen, Juan Aparicio Ojea, Alice M. Agogino, Aviv Tamar, Pieter Abbeel
2019	—	`conf`	Robust 2D Assembly Sequencing via Geometric Planning with Learned Scores. CASE Tzvika Geft, Aviv Tamar, Ken Goldberg, Dan Halperin
2019	J	`jnl`	Sub-Goal Trees - a Framework for Goal-Directed Trajectory Prediction and Optimization. CoRR Tom Jurgenson, Edward Groshev, Aviv Tamar
2018	J	`jnl`	Distributional Multivariate Policy Evaluation and Exploration with the Bellman GAN. CoRR Dror Freirich, Ron Meir, Aviv Tamar
2018	—	`conf`	Imitation Learning from Visual Data with Multiple Intentions. ICLR (Poster) Aviv Tamar, Khashayar Rohanimanesh, Yinlam Chow, Chris Vigorito, Ben Goodrich, Michael Kahane, Derik Pridmore
2018	J	`jnl`	Internet Congestion Control via Deep Reinforcement Learning. CoRR Nathan Jay, Noga H. Rotman, Philip Brighten Godfrey, Michael Schapira, Aviv Tamar
2018	A*	`conf`	Learning Generalized Reactive Policies Using Deep Neural Networks. ICAPS Edward Groshev, Maxwell Goldstein, Aviv Tamar, Siddharth Srivastava, Pieter Abbeel
2018	—	`conf`	Learning Generalized Reactive Policies using Deep Neural Networks. AAAI Spring Symposia Edward Groshev, Aviv Tamar, Maxwell Goldstein, Siddharth Srivastava, Pieter Abbeel
2018	A*	`conf`	Learning Plannable Representations with Causal InfoGAN. NeurIPS Thanard Kurutach, Aviv Tamar, Ge Yang, Stuart J. Russell, Pieter Abbeel
2018	J	`jnl`	Learning Plannable Representations with Causal InfoGAN. CoRR Thanard Kurutach, Aviv Tamar, Ge Yang, Stuart Russell, Pieter Abbeel
2018	A*	`conf`	Learning Robotic Assembly from CAD. ICRA Garrett Thomas, Melissa Chien, Aviv Tamar, Juan Aparicio Ojea, Pieter Abbeel
2018	J	`jnl`	Learning Robotic Assembly from CAD. CoRR Garrett Thomas, Melissa Chien, Aviv Tamar, Juan Aparicio Ojea, Pieter Abbeel
2018	J	`jnl`	Learning and Planning with a Semantic Model. CoRR Yi Wu, Yuxin Wu, Aviv Tamar, Stuart Russell, Georgia Gkioxari, Yuandong Tian
2018	—	`conf`	Model-Ensemble Trust-Region Policy Optimization. ICLR (Poster) Thanard Kurutach, Ignasi Clavera, Yan Duan, Aviv Tamar, Pieter Abbeel
2018	J	`jnl`	Model-Ensemble Trust-Region Policy Optimization. CoRR Thanard Kurutach, Ignasi Clavera, Yan Duan, Aviv Tamar, Pieter Abbeel
2018	J	`jnl`	Safe Policy Learning from Observations. CoRR Elad Sarafian, Aviv Tamar, Sarit Kraus
2017	J	`jnl`	A Machine Learning Approach to Routing. CoRR Asaf Valadarsky, Michael Schapira, Dafna Shahaf, Aviv Tamar
2017	A*	`conf`	Constrained Policy Optimization. ICML Joshua Achiam, David Held, Aviv Tamar, Pieter Abbeel
2017	J	`jnl`	Constrained Policy Optimization. CoRR Joshua Achiam, David Held, Aviv Tamar, Pieter Abbeel
2017	J	`jnl`	Learning Generalized Reactive Policies using Deep Neural Networks. CoRR Edward Groshev, Aviv Tamar, Siddharth Srivastava, Pieter Abbeel
2017	A*	`conf`	Learning from the hindsight plan - Episodic MPC improvement. ICRA Aviv Tamar, Garrett Thomas, Tianhao Zhang, Sergey Levine, Pieter Abbeel
2017	Misc	`conf`	Learning to Route. HotNets Asaf Valadarsky, Michael Schapira, Dafna Shahaf, Aviv Tamar
2017	—	`conf`	Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments. NIPS Ryan Lowe, Yi Wu, Aviv Tamar, Jean Harb, Pieter Abbeel, Igor Mordatch
2017	J	`jnl`	Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments. CoRR Ryan Lowe, Yi Wu, Aviv Tamar, Jean Harb, Pieter Abbeel, Igor Mordatch
2017	J	`jnl`	Safer Classification by Synthesis. CoRR William Wang, Angelina Wang, Aviv Tamar, Xi Chen, Pieter Abbeel
2017	J	`jnl`	Sequential Decision Making With Coherent Risk. IEEE Trans. Autom. Control. Aviv Tamar, Yinlam Chow, Mohammad Ghavamzadeh, Shie Mannor
2017	—	`conf`	Shallow Updates for Deep Reinforcement Learning. NIPS Nir Levine, Tom Zahavy, Daniel J. Mankowitz, Aviv Tamar, Shie Mannor
2017	J	`jnl`	Shallow Updates for Deep Reinforcement Learning. CoRR Nir Levine, Tom Zahavy, Daniel J. Mankowitz, Aviv Tamar, Shie Mannor
2017	J	`jnl`	Situationally Aware Options. CoRR Daniel J. Mankowitz, Aviv Tamar, Shie Mannor
2017	A*	`conf`	Value Iteration Networks. IJCAI Aviv Tamar, Yi Wu, Garrett Thomas, Sergey Levine, Pieter Abbeel
2016	J	`jnl`	Bayesian Reinforcement Learning: A Survey. CoRR Mohammad Ghavamzadeh, Shie Mannor, Joelle Pineau, Aviv Tamar
2016	A*	`conf`	Generalized Emphatic Temporal Difference Learning: Bias-Variance Analysis. AAAI Assaf Hallak, Aviv Tamar, Rémi Munos, Shie Mannor
2016	J	`jnl`	Learning from the Hindsight Plan - Episodic MPC Improvement. CoRR Aviv Tamar, Garrett Thomas, Tianhao Zhang, Sergey Levine, Pieter Abbeel
2016	J	`jnl`	Learning the Variance of the Reward-To-Go. J. Mach. Learn. Res. Aviv Tamar, Dotan Di Castro, Shie Mannor
2016	J	`jnl`	Situational Awareness by Risk-Conscious Skills. CoRR Daniel J. Mankowitz, Aviv Tamar, Shie Mannor
2016	—	`conf`	Value Iteration Networks. NIPS Aviv Tamar, Sergey Levine, Pieter Abbeel, Yi Wu, Garrett Thomas
2016	J	`jnl`	Value Iteration Networks. CoRR Aviv Tamar, Sergey Levine, Pieter Abbeel
2015	J	`jnl`	Bayesian Reinforcement Learning: A Survey. Found. Trends Mach. Learn. Mohammad Ghavamzadeh, Shie Mannor, Joelle Pineau, Aviv Tamar
2015	J	`jnl`	Emphatic TD Bellman Operator is a Contraction. CoRR Assaf Hallak, Aviv Tamar, Shie Mannor
2015	J	`jnl`	Generalized Emphatic Temporal Difference Learning: Bias-Variance Analysis. CoRR Assaf Hallak, Aviv Tamar, Rémi Munos, Shie Mannor
2015	A*	`conf`	Optimizing the CVaR via Sampling. AAAI Aviv Tamar, Yonatan Glassner, Shie Mannor
2015	—	`conf`	Policy Gradient for Coherent Risk Measures. NIPS Aviv Tamar, Yinlam Chow, Mohammad Ghavamzadeh, Shie Mannor
2015	J	`jnl`	Policy Gradient for Coherent Risk Measures. CoRR Aviv Tamar, Yinlam Chow, Mohammad Ghavamzadeh, Shie Mannor
2015	—	`conf`	Risk-Sensitive and Robust Decision-Making: a CVaR Optimization Approach. NIPS Yinlam Chow, Aviv Tamar, Shie Mannor, Marco Pavone
2015	J	`jnl`	Risk-Sensitive and Robust Decision-Making: a CVaR Optimization Approach. CoRR Yinlam Chow, Aviv Tamar, Shie Mannor, Marco Pavone
2014	J	`jnl`	Implicit Temporal Differences. CoRR Aviv Tamar, Panos Toulis, Shie Mannor, Edoardo M. Airoldi
2014	J	`jnl`	Policy Gradients Beyond Expectations: Conditional Value-at-Risk. CoRR Aviv Tamar, Yonatan Glassner, Shie Mannor
2014	A*	`conf`	Scaling Up Robust MDPs using Function Approximation. ICML Aviv Tamar, Shie Mannor, Huan Xu
2013	J	`jnl`	Policy Evaluation with Variance Related Risk Criteria in Markov Decision Processes CoRR Aviv Tamar, Dotan Di Castro, Shie Mannor
2013	J	`jnl`	Scaling Up Robust MDPs by Reinforcement Learning. CoRR Aviv Tamar, Huan Xu, Shie Mannor
2013	—	`conf`	Temporal Difference Methods for the Variance of the Reward To Go. ICML (3) Aviv Tamar, Dotan Di Castro, Shie Mannor
2013	J	`jnl`	Variance Adjusted Actor Critic Algorithms. CoRR Aviv Tamar, Shie Mannor
2012	J	`jnl`	Integrating a Partial Model into Model Free Reinforcement Learning. J. Mach. Learn. Res. Aviv Tamar, Dotan Di Castro, Ron Meir
2012	A*	`conf`	Policy Gradients with Variance Related Risk Criteria. ICML Dotan Di Castro, Aviv Tamar, Shie Mannor
2011	A*	`conf`	Integrating Partial Model Knowledge in Model Free RL Algorithms. ICML Aviv Tamar, Dotan Di Castro, Ron Meir