| Learn what not to learn: Action elimination with deep reinforcement learning T Zahavy, M Haroush, N Merlis, DJ Mankowitz, S Mannor arXiv preprint arXiv:1809.02121, 2018 | 254 | 2018 |
| Tight regret bounds for model-based reinforcement learning with greedy policies Y Efroni, N Merlis, M Ghavamzadeh, S Mannor Advances in Neural Information Processing Systems 32, 2019 | 79 | 2019 |
| Reinforcement learning with trajectory feedback Y Efroni, N Merlis, S Mannor Proceedings of the AAAI conference on artificial intelligence 35 (8), 7288-7295, 2021 | 45 | 2021 |
| Ensemble bootstrapping for q-learning O Peer, C Tessler, N Merlis, R Meir International Conference on Machine Learning, 8454-8463, 2021 | 42 | 2021 |
| Batch-size independent regret bounds for the combinatorial multi-armed bandit problem N Merlis, S Mannor Conference on Learning Theory, 2465-2489, 2019 | 31 | 2019 |
| Tight lower bounds for combinatorial multi-armed bandits N Merlis, S Mannor Conference on Learning Theory, 2830-2857, 2020 | 21 | 2020 |
| Confidence-budget matching for sequential budgeted learning Y Efroni, N Merlis, A Saha, S Mannor International Conference on Machine Learning, 2937-2947, 2021 | 10 | 2021 |
| Lenient regret for multi-armed bandits N Merlis, S Mannor Proceedings of the AAAI Conference on Artificial Intelligence 35 (10), 8950-8957, 2021 | 7 | 2021 |
| Reinforcement learning with history dependent dynamic contexts G Tennenholtz, N Merlis, L Shani, M Mladenov, C Boutilier International Conference on Machine Learning, 34011-34053, 2023 | 5 | 2023 |
| Reinforcement learning with a terminator G Tennenholtz, N Merlis, L Shani, S Mannor, U Shalit, G Chechik, ... Advances in Neural Information Processing Systems 35, 35696-35709, 2022 | 4 | 2022 |
| Never Worse, Mostly Better: Stable Policy Improvement in Deep Reinforcement Learning P Khanna, G Tennenholtz, N Merlis, S Mannor, C Tessler arXiv preprint arXiv:1910.01062, 2019 | 4* | 2019 |
| Multi-armed bandits with guaranteed revenue per arm D Baudry, N Merlis, MB Molina, H Richard, V Perchet International Conference on Artificial Intelligence and Statistics, 379-387, 2024 | 2 | 2024 |
| On preemption and learning in stochastic scheduling N Merlis, H Richard, F Sentenac, C Odic, M Molina, V Perchet International Conference on Machine Learning, 24478-24516, 2023 | 2 | 2023 |
| The Value of Reward Lookahead in Reinforcement Learning N Merlis, D Baudry, V Perchet arXiv preprint arXiv:2403.11637, 2024 | 1 | 2024 |
| Stable Matching with Ties: Approximation Ratios and Learning S Lin, S Mauras, N Merlis, V Perchet arXiv preprint arXiv:2411.03270, 2024 | | 2024 |
| Improved Algorithms for Contextual Dynamic Pricing M Tullii, S Gaucher, N Merlis, V Perchet arXiv preprint arXiv:2406.11316, 2024 | | 2024 |
| Reinforcement Learning with Lookahead Information N Merlis arXiv preprint arXiv:2406.02258, 2024 | | 2024 |
| On Bits and Bandits: Quantifying the Regret-Information Trade-off I Shufaro, N Merlis, N Weinberger, S Mannor arXiv preprint arXiv:2405.16581, 2024 | | 2024 |
| Ranking with Popularity Bias: User Welfare under Self-Amplification Dynamics G Tennenholtz, M Mladenov, N Merlis, RL Axtell, C Boutilier arXiv preprint arXiv:2305.18333, 2023 | | 2023 |
| Query-Reward Tradeoffs in Multi-Armed Bandits N Merlis, Y Efroni, S Mannor arXiv preprint arXiv:2110.05724, 2021 | | 2021 |
Shie MannorProfessor of Electrical Engineering @ Technion & Researcher @ NvidiaVerified email at technion.ac.il
