Publications

2021

Efficient Self-Supervised Data Collection for Offline Robot Learning
Shadi Endrawis, Gal Leibovich, Guy Jacob, Gal Novik and Aviv Tamar
Published in ICRA 2021
Paper

Unsupervised Feature Learning for Manipulation with Contrastive Domain Randomization
Carmel Rabinovitz, Niko Grupen and Aviv Tamar
Published in ICRA 2021
Paper

Action Redundancy in Reinforcement Learning
Nir Baram, Guy Tennenholtz and Shie Mannor
Published in UAI 2021
Paper

Bandits with Partially Observable Confounded Data
Guy Tennenholtz, Uri Shalit, Shie Mannor and Yonathan Efroni
Published in UAI 2021
Paper

Ensemble Bootstrapping for Q-Learning
Oren Peer, Chen Tessler, Nadav Merlis and Ron Meir
Published in ICML 2021
Paper

Detecting Rewards Deterioration in Episodic Reinforcement Learning
Ido Greenberg and Shie Mannor
Published in ICML 2021
Paper

Confidence-Budget Matching for Sequential Budgeted Learning
Yonathan Efroni, Nadav Merlis, Aadirupa Saha and Shie Mannor
Published in ICML 2021
Paper

Online Limited Memory Neural-Linear Bandits with Likelihood Matching
Ofir Nabati, Tom Zahavy and Shie Mannor
Published in ICML 2021
Paper

Acting in Delayed Environments with Non-Stationary Markov Policies
Ester Derman, Gal Dalal and Shie Mannor
Published in ICLR 2021
Paper

Optimizing Memory Placement using Evolutionary Graph Reinforcement Learning
Shauharda Khadka, Estelle Aflalo, Mattias Marder, Avrech Ben-David, Santiago Miret, Shie Mannor, Tamir Hazan, Hanlin Tang and Somdeb Majumdar
Published in ICLR 2021
Paper

Lenient Regret for Multi-Armed Bandits
Nadav Merlis and Shie Mannor
Published in AAAI 2021
Paper

Reinforcement Learning with Trajectory Feedback
Yonathan Efroni, Nadav Merlis and Shie Mannor
Published in AAAI 2021
Paper

Inverse Reinforcement Learning in Contextual MDPs
Stav Belogolovsky, Philip Korsunsky, Shie Mannor, Chen Tessler and Tom Zahavy
Published in Springer Machine Learning Journal, RL for Real Life (special eddition)
Paper

2020

Tight lower bounds for combinatorial multi-armed bandits
Nadav Merlis and Shie Mannor
Published in COLT 2020
Paper, Video

Optimistic Policy Optimization with Bandit Feedback
Lior Shani, Yonathan Efroni, Aviv Rosenberg, Shie Mannor
Published in ICML 2020
Paper

Discount Factor as a Regularizer in Reinforcement Learning
Ron Amit, Ron Meir and Kamil Ciosek
Published in ICML 2020
Paper, Code, Slides, Video

Option Discovery in the Absence of Rewards with Manifold Analysis
Amitay Bar, Ronen Talmon, and Ron Meir
Published in ICML 2020
Paper

Sub-Goal Trees a Framework for Goal-Based Reinforcement Learning
Tom Jurgenson, Or Avner, Edward Groshev, Aviv Tamar
Published in ICML 2020
Paper, Code

Adaptive Trust Region Policy Optimization: Global Convergence and Faster Rates for Regularized MDPs
Lior Shani*, Yonathan Efroni* and Shie Mannor
Published in AAAI 2020 – oral
Paper

Off-Policy Evaluation in Partially Observable Environments
Guy Tennenholtz, Shie Mannor and Uri Shalit
Published in AAAI 2020 – oral
Paper

2019

Multi Agent Reinforcement Learning with Multi-Step Generative Models
Orr Krupnik, Igor Mordatch and Aviv Tamar
Published in CoRL 2019
Paper

Distributional Policy Optimization: An Alternative Approach for Continuous Control
Chen Tessler*, Guy Tennenholtz* and Shie Mannor
Published in NeurIPS 2019
Paper, Code

Tight Regret Bounds for Model-Based Reinforcement Learning with Greedy Policies
Yonathan Efroni*,Nadav Merlis*, Mohammad Ghavamzadeh and Shie Mannor
Published in NeurIPS 2019 – spotlight
Paper

A Bayesian Approach to Robust Reinforcement Learning
Esther Derman, Daniel J. Mankowitz, Timothy A. Mann and Shie Mannor
Published in UAI 2019 – oral
Paper, Video

Action Robust Reinforcement Learning and Applications in Continuous Control
Chen Tessler*, Yonathan Efroni* and Shie Mannor
Published in ICML 2019
Paper, Code

Exploration Conscious Reinforcement Learning Revisited
Lior Shani*, Yonathan Efroni* and Shie Mannor
Published in ICML 2019
Paper

The Natural Language of Actions
Guy Tennenholtz and Shie Mannor
Published in ICML 2019 – oral
Paper, Video

Distributional multivariate policy evaluation and exploration with the Bellman GAN
Dror Freirich, Tzahi Shimkin, Ron Meir, Aviv Tamar
Published in ICML 2019
Paper

Batch-Size Independent Regret Bounds for the Combinatorial Multi-Armed Bandit Problem
Nadav Merlis and Shie Mannor
Published in COLT 2019
Paper

Harnessing Reinforcement Learning for Neural Motion Planning
Tom Jurgenson and Aviv Tamar
Published in RSS 2019
Paper

Reward Constrained Policy Optimization
Chen Tessler, Daniel J. Mankowitz and Shie Mannor
Published in ICLR 2019
Paper

How to Combine Tree-Search Methods in Reinforcement Learning
Yonathan Efroni, Gal Dalal, Bruno Scherrer and Shie Mannor
Published in AAAI 2019 – best paper award
Paper

2018

Learn What Not to Learn: Action Elimination with Deep Reinforcement Learning
Tom Zahavy*, Matan Haroush*, Nadav Merlis*, Daniel J. Mankowitz and Shie Mannor
Published in NeurIPS 2018
Paper, Code

Multiple-Step Greedy Policies in Approximate and Online Reinforcement Learning
Yonathan Efroni, Gal Dalal, Bruno Scherrer and Shie Mannor
Published in NeurIPS 2018 – spotlight
Paper

Soft-Robust Actor-Critic Policy-Gradient
Esther Derman, Daniel J. Mankowitz, Timothy A. Mann and Shie Mannor
Published in UAI 2018
Paper

Beyond the One-Step Greedy Approach in Reinforcement Learning
Yonathan Efroni, Gal Dalal, Bruno Scherrer and Shie Mannor
Published in ICML 2018 – oral
Paper

Meta-Learning by Adjusting Priors Based on Extended PAC-Bayes Theory
Ron Amit and Ron Meir
Published in ICML 2018 – oral
Paper, Code, Video

2017

A Deep Hierarchical Approach to Lifelong Learning in Minecraft
Chen Tessler*, Shahar Givony*, Tom Zahavy*, Daniel J. Mankowitz* and Shie Mannor
Published in AAAI 2017
Paper, Code