Nadav Merlis

According to our database, Nadav Merlis authored at least 20 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Improved Algorithms for Contextual Dynamic Pricing.

Matilde Tullii, Solenne Gaucher, Nadav Merlis, Vianney Perchet

CoRR, 2024

Reinforcement Learning with Lookahead Information.

Nadav Merlis

CoRR, 2024

On Bits and Bandits: Quantifying the Regret-Information Trade-off.

Itai Shufaro, Nadav Merlis, Nir Weinberger, Shie Mannor

CoRR, 2024

The Value of Reward Lookahead in Reinforcement Learning.

Nadav Merlis, Dorian Baudry, Vianney Perchet

CoRR, 2024

Multi-armed bandits with guaranteed revenue per arm.

Dorian Baudry, Nadav Merlis, Mathieu Benjamin Molina, Hugo Richard, Vianney Perchet

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Ranking with Popularity Bias: User Welfare under Self-Amplification Dynamics.

Guy Tennenholtz, Martin Mladenov, Nadav Merlis, Craig Boutilier

CoRR, 2023

Reinforcement Learning with History Dependent Dynamic Contexts.

Guy Tennenholtz, Nadav Merlis, Lior Shani, Martin Mladenov, Craig Boutilier

Proceedings of the International Conference on Machine Learning, 2023

On Preemption and Learning in Stochastic Scheduling.

Nadav Merlis, Hugo Richard, Flore Sentenac, Corentin Odic, Mathieu Molina, Vianney Perchet

Proceedings of the International Conference on Machine Learning, 2023

Never Worse, Mostly Better: Stable Policy Improvement in Deep Reinforcement Learning.

Pranav Khanna, Guy Tennenholtz, Nadav Merlis, Shie Mannor, Chen Tessler

Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023

2022

Reinforcement Learning with a Terminator.

Guy Tennenholtz, Nadav Merlis, Lior Shani, Shie Mannor, Uri Shalit, Gal Chechik, Assaf Hallak, Gal Dalal

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Dare not to Ask: Problem-Dependent Guarantees for Budgeted Bandits.

Nadav Merlis, Yonathan Efroni, Shie Mannor

CoRR, 2021

Ensemble Bootstrapping for Q-Learning.

Oren Peer, Chen Tessler, Nadav Merlis, Ron Meir

Proceedings of the 38th International Conference on Machine Learning, 2021

Confidence-Budget Matching for Sequential Budgeted Learning.

Yonathan Efroni, Nadav Merlis, Aadirupa Saha, Shie Mannor

Proceedings of the 38th International Conference on Machine Learning, 2021

Lenient Regret for Multi-Armed Bandits.

Nadav Merlis, Shie Mannor

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Reinforcement Learning with Trajectory Feedback.

Yonathan Efroni, Nadav Merlis, Shie Mannor

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Tight Lower Bounds for Combinatorial Multi-Armed Bandits.

Nadav Merlis, Shie Mannor

Proceedings of the Conference on Learning Theory, 2020

2019

Stabilizing Off-Policy Reinforcement Learning with Conservative Policy Gradients.

Chen Tessler, Nadav Merlis, Shie Mannor

CoRR, 2019

Tight Regret Bounds for Model-Based Reinforcement Learning with Greedy Policies.

Yonathan Efroni, Nadav Merlis, Mohammad Ghavamzadeh, Shie Mannor

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Batch-Size Independent Regret Bounds for the Combinatorial Multi-Armed Bandit Problem.

Nadav Merlis, Shie Mannor

Proceedings of the Conference on Learning Theory, 2019

2018

Learn What Not to Learn: Action Elimination with Deep Reinforcement Learning.

Tom Zahavy, Matan Haroush, Nadav Merlis, Daniel J. Mankowitz, Shie Mannor

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018