| 2025 | ICLR | Building Math Agents with Multi-Turn Iterative Preference Learning. | Wei Xiong, Chengshuai Shi, Jiaming Shen, Aviv Rosenberg, Zhen Qin, Daniele Calandriello, Misha Khalman, Rishabh Joshi, Bilal Piot, Mohammad Saleh, Chi Jin, Tong Zhang, Tianqi Liu |
| 2024 | AISTATS | Vector Quantile Regression on Manifolds. | Marco Pegoraro, Sanketh Vedula, Aviv Rosenberg, Irene Tallini, Emanuele Rodol, Alex M. Bronstein |
| 2024 | ICML | Near-Optimal Regret in Linear MDPs with Aggregate Bandit Feedback. | Asaf Cassel, Haipeng Luo, Aviv Rosenberg, Dmitry Sotnikov |
| 2023 | AAAI | Planning and Learning with Adaptive Lookahead. | Aviv Rosenberg, Assaf Hallak, Shie Mannor, Gal Chechik, Gal Dalal |
| 2023 | COLT | A Unified Analysis of Nonstochastic Delayed Feedback for Combinatorial Semi-Bandits, Linear Bandits, and MDPs. | Dirk van der Hoeven, Lukas Zierahn, Tal Lancewicki, Aviv Rosenberg, Nicol Cesa-Bianchi |
| 2023 | ICML | Delay-Adapted Policy Optimization and Improved Regret for Adversarial MDP with Delayed Bandit Feedback. | Tal Lancewicki, Aviv Rosenberg, Dmitry Sotnikov |
| 2022 | AAAI | Learning Adversarial Markov Decision Processes with Delayed Feedback. | Tal Lancewicki, Aviv Rosenberg, Yishay Mansour |
| 2022 | COLT | Policy Optimization for Stochastic Shortest Path. | Liyu Chen, Haipeng Luo, Aviv Rosenberg |
| 2022 | ICML | Cooperative Online Learning in Stochastic and Adversarial MDPs. | Tal Lancewicki, Aviv Rosenberg, Yishay Mansour |
| 2021 | IJCAI | Stochastic Shortest Path with Adversarially Changing Costs. | Aviv Rosenberg, Yishay Mansour |
| 2020 | ICML | Near-optimal Regret Bounds for Stochastic Shortest Path. | Aviv Rosenberg, Alon Cohen, Yishay Mansour, Haim Kaplan |
| 2020 | ICML | Optimistic Policy Optimization with Bandit Feedback. | Lior Shani, Yonathan Efroni, Aviv Rosenberg, Shie Mannor |
| 2019 | ICML | Online Convex Optimization in Adversarial Markov Decision Processes. | Aviv Rosenberg, Yishay Mansour |