Beyond the One-Step Greedy Approach in Reinforcement Learning. - Yonathan Efroni; Gal Dalal; Bruno Scherrer; Shie Mannor (ICML, 2018)

Multiple-Step Greedy Policies in Approximate and Online Reinforcement Learning. - Yonathan Efroni; Gal Dalal; Bruno Scherrer; Shie Mannor (NeurIPS, 2018)

Multiple-Step Greedy Policies in Online and Approximate Reinforcement Learning. - Yonathan Efroni; Gal Dalal; Bruno Scherrer; Shie Mannor (CoRR, 2018)

Revisiting Exploration-Conscious Reinforcement Learning. - Lior Shani; Yonathan Efroni; Shie Mannor (CoRR, 2018)

How to Combine Tree-Search Methods in Reinforcement Learning. - Yonathan Efroni; Gal Dalal; Bruno Scherrer; Shie Mannor (AAAI, 2019)

Exploration Conscious Reinforcement Learning Revisited. - Lior Shani; Yonathan Efroni; Shie Mannor (ICML, 2019)

Action Robust Reinforcement Learning and Applications in Continuous Control. - Chen Tessler; Yonathan Efroni; Shie Mannor (ICML, 2019)

Tight Regret Bounds for Model-Based Reinforcement Learning with Greedy Policies. - Yonathan Efroni; Nadav Merlis; Mohammad Ghavamzadeh; Shie Mannor (NeurIPS, 2019)

Multi-Step Greedy and Approximate Real Time Dynamic Programming. - Yonathan Efroni; Mohammad Ghavamzadeh; Shie Mannor (CoRR, 2019)

Multi-step Greedy Policies in Model-Free Deep Reinforcement Learning. - Manan Tomar; Yonathan Efroni; Mohammad Ghavamzadeh (CoRR, 2019)

Adaptive Trust Region Policy Optimization: Global Convergence and Faster Rates for Regularized MDPs. - Lior Shani; Yonathan Efroni; Shie Mannor (AAAI, 2020)

Optimistic Policy Optimization with Bandit Feedback. - Lior Shani; Yonathan Efroni; Aviv Rosenberg 002; Shie Mannor (ICML, 2020)

Multi-step Greedy Reinforcement Learning Algorithms. - Manan Tomar; Yonathan Efroni; Mohammad Ghavamzadeh (ICML, 2020)

Online Planning with Lookahead Policies. - Yonathan Efroni; Mohammad Ghavamzadeh; Shie Mannor (NeurIPS, 2020)

Exploration-Exploitation in Constrained MDPs. - Yonathan Efroni; Shie Mannor; Matteo Pirotta (CoRR, 2020)

Bandits with Partially Observable Offline Data. - Guy Tennenholtz; Uri Shalit; Shie Mannor; Yonathan Efroni (CoRR, 2020)

Reinforcement Learning with Trajectory Feedback. - Yonathan Efroni; Nadav Merlis; Shie Mannor (AAAI, 2021)

Confidence-Budget Matching for Sequential Budgeted Learning. - Yonathan Efroni; Nadav Merlis; Aadirupa Saha; Shie Mannor (ICML, 2021)

Minimax Regret for Stochastic Shortest Path. - Alon Cohen; Yonathan Efroni; Yishay Mansour; Aviv Rosenberg 002 (NeurIPS, 2021)

Reinforcement Learning in Reward-Mixing MDPs. - Jeongyeol Kwon; Yonathan Efroni; Constantine Caramanis; Shie Mannor (NeurIPS, 2021)

RL for Latent MDPs: Regret Guarantees and a Lower Bound. - Jeongyeol Kwon; Yonathan Efroni; Constantine Caramanis; Shie Mannor (NeurIPS, 2021)

Bandits with partially observable confounded data. - Guy Tennenholtz; Uri Shalit; Shie Mannor; Yonathan Efroni (UAI, 2021)

Dare not to Ask: Problem-Dependent Guarantees for Budgeted Bandits. - Nadav Merlis; Yonathan Efroni; Shie Mannor (CoRR, 2021)

Provable RL with Exogenous Distractors via Multistep Inverse Dynamics. - Yonathan Efroni; Dipendra Misra; Akshay Krishnamurthy; Alekh Agarwal; John Langford 001 (CoRR, 2021)

Sample-Efficient Reinforcement Learning in the Presence of Exogenous Information. - Yonathan Efroni; Dylan J. Foster; Dipendra Misra; Akshay Krishnamurthy; John Langford 001 (COLT, 2022)

Provably Filtering Exogenous Distractors using Multistep Inverse Dynamics. - Yonathan Efroni; Dipendra Misra; Akshay Krishnamurthy; Alekh Agarwal; John Langford 001 (ICLR, 2022)

Mirror Descent Policy Optimization. - Manan Tomar; Lior Shani; Yonathan Efroni; Mohammad Ghavamzadeh (ICLR, 2022)

Provable Reinforcement Learning with a Short-Term Memory. - Yonathan Efroni; Chi Jin 001; Akshay Krishnamurthy; Sobhan Miryoosefi (ICML, 2022)

Sparsity in Partially Controllable Linear Systems. - Yonathan Efroni; Sham M. Kakade; Akshay Krishnamurthy; Cyril Zhang (ICML, 2022)

Coordinated Attacks against Contextual Bandits: Fundamental Limits and Defense Mechanisms. - Jeongyeol Kwon; Yonathan Efroni; Constantine Caramanis; Shie Mannor (ICML, 2022)

Tractable Optimality in Episodic Latent MABs. - Jeongyeol Kwon; Yonathan Efroni; Constantine Caramanis; Shie Mannor (NeurIPS, 2022)

Guaranteed Discovery of Controllable Latent States with Multi-Step Inverse Models. - Alex Lamb; Riashat Islam; Yonathan Efroni; Aniket Didolkar; Dipendra Misra; Dylan J. Foster; Lekan P. Molu; Rajan Chari; Akshay Krishnamurthy; John Langford 001 (CoRR, 2022)

Agent-Controller Representations: Principled Offline RL with Rich Exogenous Information. - Riashat Islam; Manan Tomar; Alex Lamb; Yonathan Efroni; Hongyu Zang; Aniket Didolkar; Dipendra Misra; Xin Li 033; Harm van Seijen; Remi Tachet des Combes; John Langford 001 (CoRR, 2022)

Principled Offline RL in the Presence of Rich Exogenous Information. - Riashat Islam; Manan Tomar; Alex Lamb; Yonathan Efroni; Hongyu Zang; Aniket Rajiv Didolkar; Dipendra Misra; Xin Li 033; Harm van Seijen; Remi Tachet des Combes; John Langford 001 (ICML, 2023)

Reward-Mixing MDPs with Few Latent Contexts are Learnable. - Jeongyeol Kwon; Yonathan Efroni; Constantine Caramanis; Shie Mannor (ICML, 2023)

Pearl: A Production-ready Reinforcement Learning Agent. - Zheqing Zhu; Rodrigo de Salvo Braz; Jalaj Bhandari; Daniel Jiang; Yi Wan; Yonathan Efroni; Liyuan Wang; Ruiyang Xu; Hongbo Guo; Alex Nikulkov; Dmytro Korenkevych; Ürün Dogan; et al. (CoRR, 2023)

Guaranteed Discovery of Control-Endogenous Latent States with Multi-Step Inverse Models. - Alex Lamb; Riashat Islam; Yonathan Efroni; Aniket Rajiv Didolkar; Dipendra Misra; Dylan J. Foster; Lekan P. Molu; Rajan Chari; Akshay Krishnamurthy; John Langford 001 (Trans. Mach. Learn. Res., 2023)

PcLast: Discovering Plannable Continuous Latent States. - Anurag Koul; Shivakanth Sujit; Shaoru Chen; Ben Evans; Lili Wu; Byron Xu; Rajan Chari; Riashat Islam; Raihan Seraj; Yonathan Efroni; Lekan P. Molu; Miroslav Dudík; et al. (ICML, 2024)

Prospective Side Information for Latent MDPs. - Jeongyeol Kwon; Yonathan Efroni; Shie Mannor; Constantine Caramanis (ICML, 2024)

RL in Latent MDPs is Tractable: Online Guarantees via Off-Policy Evaluation. - Jeongyeol Kwon; Shie Mannor; Constantine Caramanis; Yonathan Efroni (NeurIPS, 2024)

The Bias of Harmful Label Associations in Vision-Language Models. - Caner Hazirbas; Alicia Sun; Yonathan Efroni; Mark Ibrahim (CoRR, 2024)

Generalizing Multi-Step Inverse Models for Representation Learning to Finite-Memory POMDPs. - Lili Wu; Ben Evans; Riashat Islam; Raihan Seraj; Yonathan Efroni; Alex Lamb (CoRR, 2024)

Exploiting Structure in Offline Multi-Agent RL: The Benefits of Low Interaction Rank. - Wenhao Zhan; Scott Fujimoto; Zheqing Zhu; Jason D. Lee; Daniel R. Jiang; Yonathan Efroni (CoRR, 2024)

Time After Time: Deep-Q Effect Estimation for Interventions on When and What to do. - Yoav Wald; Mark Goldstein; Yonathan Efroni; Wouter A. C. van Amsterdam; Rajesh Ranganath (ICLR, 2025)

Exploiting Structure in Offline Multi-Agent RL: The Benefits of Low Interaction Rank. - Wenhao Zhan; Scott Fujimoto; Zheqing Zhu; Jason D. Lee; Daniel Jiang; Yonathan Efroni (ICLR, 2025)

Aligned Multi Objective Optimization. - Yonathan Efroni; Ben Kertzu; Daniel Jiang; Jalaj Bhandari; Zheqing Zhu; Karen Ullrich (CoRR, 2025)