| 2025 | ICLR | Regret-Optimal List Replicable Bandit Learning: Matching Upper and Lower Bounds. | Michael Chen, Aduri Pavan, N. V. Vinodchandran, Ruosong Wang, Lin Yang |
| 2025 | ICLR | Misspecified Q-Learning with Sparse Linear Function Approximation: Tight Bounds on Approximation Error. | Ally Yalei Du, Lin Yang, Ruosong Wang |
| 2025 | ICML | Minimax Optimal Regret Bound for Reinforcement Learning with Trajectory Feedback. | Zihan Zhang, Yuxin Chen, Jason D. Lee, Simon Shaolei Du, Ruosong Wang |
| 2023 | AISTATS | Provably Efficient Reinforcement Learning via Surprise Bound. | Hanlin Zhu, Ruosong Wang, Jason D. Lee |
| 2023 | ICLR | Variance-Aware Sparse Linear Bandits. | Yan Dai, Ruosong Wang, Simon Shaolei Du |
| 2023 | ICML | Horizon-Free and Variance-Dependent Reinforcement Learning for Latent Markov Decision Processes. | Runlong Zhou, Ruosong Wang, Simon Shaolei Du |
| 2021 | FOCS | Settling the Horizon-Dependence of Sample Complexity in Reinforcement Learning. | Yuanzhi Li, Ruosong Wang, Lin F. Yang |
| 2021 | ICLR | Optimism in Reinforcement Learning with Generalized Linear Function Approximation. | Yining Wang, Ruosong Wang, Simon Shaolei Du, Akshay Krishnamurthy |
| 2021 | ICLR | What are the Statistical Limits of Offline RL with Linear Function Approximation? | Ruosong Wang, Dean P. Foster, Sham M. Kakade |
| 2021 | ICML | Bilinear Classes: A Structural Framework for Provable Generalization in RL. | Simon S. Du, Sham M. Kakade, Jason D. Lee, Shachar Lovett, Gaurav Mahajan, Wen Sun, Ruosong Wang |
| 2021 | ICML | Instabilities of Offline RL with Pre-Trained Neural Representation. | Ruosong Wang, Yifan Wu, Ruslan Salakhutdinov, Sham M. Kakade |
| 2020 | ICLR | Harnessing the Power of Infinitely Wide Deep Nets on Small-data Tasks. | Sanjeev Arora, Simon S. Du, Zhiyuan Li, Ruslan Salakhutdinov, Ruosong Wang, Dingli Yu |
| 2020 | ICLR | Is a Good Representation Sufficient for Sample Efficient Reinforcement Learning? | Simon S. Du, Sham M. Kakade, Ruosong Wang, Lin F. Yang |
| 2020 | ICML | Nearly Linear Row Sampling Algorithm for Quantile Regression. | Yi Li, Ruosong Wang, Lin Yang, Hanrui Zhang |
| 2020 | SODA | Tight Bounds for the Subspace Sketch Problem with Applications. | Yi Li, Ruosong Wang, David P. Woodruff |
| 2020 | SODA | The Communication Complexity of Optimization. | Santosh S. Vempala, Ruosong Wang, David P. Woodruff |
| 2019 | ICML | Fine-Grained Analysis of Optimization and Generalization for Overparameterized Two-Layer Neural Networks. | Sanjeev Arora, Simon S. Du, Wei Hu, Zhiyuan Li, Ruosong Wang |
| 2019 | ICML | Dimensionality Reduction for Tukey Regression. | Kenneth L. Clarkson, Ruosong Wang, David P. Woodruff |
| 2019 | SODA | Tight Bounds for ℓp Oblivious Subspace Embeddings. | Ruosong Wang, David P. Woodruff |
| 2017 | AAAI | Bounded Rationality of Restricted Turing Machines. | Lijie Chen, Pingzhong Tang, Ruosong Wang |
| 2017 | COLT | Nearly Optimal Sampling Algorithms for Combinatorial Pure Exploration. | Lijie Chen, Anupam Gupta, Jian Li, Mingda Qiao, Ruosong Wang |
| 2017 | ICDT | k-Regret Minimizing Set: Efficient Algorithms and Hardness. | Wei Cao, Jian Li, Haitao Wang, Kangning Wang, Ruosong Wang, Raymond Chi-Wing Wong, Wei Zhan |
| 2017 | STOC | Exponential separations in the energy complexity of leader election. | Yi-Jun Chang, Tsvi Kopelowitz, Seth Pettie, Ruosong Wang, Wei Zhan |