| 2025 | COLT | Decision Making in Hybrid Environments: A Model Aggregation Approach. | Haolin Liu, Chen-Yu Wei, Julian Zimmert |
| 2025 | WWW | A Scalable Crawling Algorithm Utilizing Noisy Change-Indicating Signals. | Julian Zimmert, Rbert Busa-Fekete, Andrs Gyrgy, Linhai Qiu, Hyomin Choi, Tzu-Wei Sung, Hao Shen, Sharmila Subramaniam, Li Xiao |
| 2024 | ICLR | Towards Optimal Regret in Adversarial Linear MDPs with Bandit Feedback. | Haolin Liu, Chen-Yu Wei, Julian Zimmert |
| 2023 | ALT | A Unified Algorithm for Stochastic Path Problems. | Christoph Dann, Chen-Yu Wei, Julian Zimmert |
| 2023 | COLT | A Blackbox Approach to Best of Both Worlds in Bandits and Beyond. | Christoph Dann, Chen-Yu Wei, Julian Zimmert |
| 2023 | ICML | Refined Regret for Adversarial MDPs with Linear Function Approximation. | Yan Dai, Haipeng Luo, Chen-Yu Wei, Julian Zimmert |
| 2023 | ICML | Best of Both Worlds Policy Optimization. | Christoph Dann, Chen-Yu Wei, Julian Zimmert |
| 2022 | ALT | Efficient Methods for Online Multiclass Logistic Regression. | Naman Agarwal, Satyen Kale, Julian Zimmert |
| 2022 | ALT | A Model Selection Approach for Corruption Robust Reinforcement Learning. | Chen-Yu Wei, Christoph Dann, Julian Zimmert |
| 2022 | COLT | Pushing the Efficiency-Regret Pareto Frontier for Online Learning of Portfolios and Quantum States. | Julian Zimmert, Naman Agarwal, Satyen Kale |
| 2022 | COLT | Return of the bias: Almost minimax optimal high probability bounds for adversarial linear bandits. | Julian Zimmert, Tor Lattimore |
| 2020 | AISTATS | An Optimal Algorithm for Adversarial Bandits with Arbitrary Delays. | Julian Zimmert, Yevgeny Seldin |
| 2020 | ICML | Online Learning for Active Cache Synchronization. | Andrey Kolobov, Sbastien Bubeck, Julian Zimmert |
| 2019 | AISTATS | An Optimal Algorithm for Stochastic and Adversarial Bandits. | Julian Zimmert, Yevgeny Seldin |
| 2019 | ICML | Beating Stochastic and Adversarial Semi-bandits Optimally and Simultaneously. | Julian Zimmert, Haipeng Luo, Chen-Yu Wei |