Ruosong Wang - RankMe

81 papers A* 34A 5Journal 41Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Frozen Policy Iteration: Computationally Efficient RL under Linear Q CoRR Yijing Ke, Zihan Zhang, Ruosong Wang
2025	J	`jnl`	List Replicable Reinforcement Learning. CoRR Bohan Zhang, Michael Chen, A. Pavan, N. V. Vinodchandran, Lin F. Yang, Ruosong Wang
2025	A*	`conf`	Minimax Optimal Regret Bound for Reinforcement Learning with Trajectory Feedback. ICML Zihan Zhang, Yuxin Chen, Jason D. Lee, Simon Shaolei Du, Ruosong Wang
2025	A*	`conf`	Misspecified Q-Learning with Sparse Linear Function Approximation: Tight Bounds on Approximation Error. ICLR Ally Yalei Du, Lin Yang, Ruosong Wang
2025	A*	`conf`	Regret-Optimal List Replicable Bandit Learning: Matching Upper and Lower Bounds. ICLR Michael Chen, Aduri Pavan, N. V. Vinodchandran, Ruosong Wang, Lin Yang
2024	J	`jnl`	Misspecified Q-Learning with Sparse Linear Function Approximation: Tight Bounds on Approximation Error. CoRR Ally Yalei Du, Lin F. Yang, Ruosong Wang
2024	A*	`conf`	Uniform Last-Iterate Guarantee for Bandits and Reinforcement Learning. NeurIPS Junyan Liu, Yunfan Li, Ruosong Wang, Lin Yang
2023	A*	`conf`	Horizon-Free and Variance-Dependent Reinforcement Learning for Latent Markov Decision Processes. ICML Runlong Zhou, Ruosong Wang, Simon Shaolei Du
2023	A	`conf`	Provably Efficient Reinforcement Learning via Surprise Bound. AISTATS Hanlin Zhu, Ruosong Wang, Jason D. Lee
2023	J	`jnl`	Provably Efficient Reinforcement Learning via Surprise Bound. CoRR Hanlin Zhu, Ruosong Wang, Jason D. Lee
2023	A*	`conf`	Variance-Aware Sparse Linear Bandits. ICLR Yan Dai, Ruosong Wang, Simon Shaolei Du
2022	J	`jnl`	Horizon-Free Reinforcement Learning for Latent Markov Decision Processes. CoRR Runlong Zhou, Ruosong Wang, Simon S. Du
2022	J	`jnl`	Tight Bounds for ℓ ACM Trans. Algorithms Ruosong Wang, David P. Woodruff
2022	J	`jnl`	Variance-Aware Sparse Linear Bandits. CoRR Yan Dai, Ruosong Wang, Simon S. Du
2021	A*	`conf`	An Exponential Lower Bound for Linearly Realizable MDP with Constant Suboptimality Gap. NeurIPS Yuanhao Wang, Ruosong Wang, Sham M. Kakade
2021	J	`jnl`	An Exponential Lower Bound for Linearly-Realizable MDPs with Constant Suboptimality Gap. CoRR Yuanhao Wang, Ruosong Wang, Sham M. Kakade
2021	A*	`conf`	Bilinear Classes: A Structural Framework for Provable Generalization in RL. ICML Simon S. Du, Sham M. Kakade, Jason D. Lee, Shachar Lovett, Gaurav Mahajan, Wen Sun, Ruosong Wang
2021	J	`jnl`	Bilinear Classes: A Structural Framework for Provable Generalization in RL. CoRR Simon S. Du, Sham M. Kakade, Jason D. Lee, Shachar Lovett, Gaurav Mahajan, Wen Sun, Ruosong Wang
2021	A*	`conf`	Instabilities of Offline RL with Pre-Trained Neural Representation. ICML Ruosong Wang, Yifan Wu, Ruslan Salakhutdinov, Sham M. Kakade
2021	J	`jnl`	Instabilities of Offline RL with Pre-Trained Neural Representation. CoRR Ruosong Wang, Yifan Wu, Ruslan Salakhutdinov, Sham M. Kakade
2021	J	`jnl`	Online Sub-Sampling for Reinforcement Learning with General Function Approximation. CoRR Dingwen Kong, Ruslan Salakhutdinov, Ruosong Wang, Lin F. Yang
2021	A*	`conf`	Optimism in Reinforcement Learning with Generalized Linear Function Approximation. ICLR Yining Wang, Ruosong Wang, Simon Shaolei Du, Akshay Krishnamurthy
2021	A*	`conf`	Settling the Horizon-Dependence of Sample Complexity in Reinforcement Learning. FOCS Yuanzhi Li, Ruosong Wang, Lin F. Yang
2021	J	`jnl`	Settling the Horizon-Dependence of Sample Complexity in Reinforcement Learning. CoRR Yuanzhi Li, Ruosong Wang, Lin F. Yang
2021	J	`jnl`	Tight Bounds for the Subspace Sketch Problem with Applications. SIAM J. Comput. Yi Li, Ruosong Wang, David P. Woodruff
2021	A*	`conf`	What are the Statistical Limits of Offline RL with Linear Function Approximation? ICLR Ruosong Wang, Dean P. Foster, Sham M. Kakade
2020	A*	`conf`	Agnostic $Q$-learning with Function Approximation in Deterministic Systems: Near-Optimal Bounds on Approximation Error and Sample Complexity. NeurIPS Simon S. Du, Jason D. Lee, Gaurav Mahajan, Ruosong Wang
2020	J	`jnl`	Agnostic Q-learning with Function Approximation in Deterministic Systems: Tight Bounds on Approximation Error and Sample Complexity. CoRR Simon S. Du, Jason D. Lee, Gaurav Mahajan, Ruosong Wang
2020	A*	`conf`	Harnessing the Power of Infinitely Wide Deep Nets on Small-data Tasks. ICLR Sanjeev Arora, Simon S. Du, Zhiyuan Li, Ruslan Salakhutdinov, Ruosong Wang, Dingli Yu
2020	A*	`conf`	Is Long Horizon RL More Difficult Than Short Horizon RL? NeurIPS Ruosong Wang, Simon S. Du, Lin F. Yang, Sham M. Kakade
2020	J	`jnl`	Is Long Horizon Reinforcement Learning More Difficult Than Short Horizon Reinforcement Learning? CoRR Ruosong Wang, Simon S. Du, Lin F. Yang, Sham M. Kakade
2020	A*	`conf`	Is a Good Representation Sufficient for Sample Efficient Reinforcement Learning? ICLR Simon S. Du, Sham M. Kakade, Ruosong Wang, Lin F. Yang
2020	A*	`conf`	Nearly Linear Row Sampling Algorithm for Quantile Regression. ICML Yi Li, Ruosong Wang, Lin Yang, Hanrui Zhang
2020	J	`jnl`	Nearly Linear Row Sampling Algorithm for Quantile Regression. CoRR Yi Li, Ruosong Wang, Lin Yang, Hanrui Zhang
2020	A*	`conf`	On Reward-Free Reinforcement Learning with Linear Function Approximation. NeurIPS Ruosong Wang, Simon S. Du, Lin F. Yang, Ruslan Salakhutdinov
2020	J	`jnl`	On Reward-Free Reinforcement Learning with Linear Function Approximation. CoRR Ruosong Wang, Simon S. Du, Lin F. Yang, Ruslan Salakhutdinov
2020	A*	`conf`	Planning with General Objective Functions: Going Beyond Total Rewards. NeurIPS Ruosong Wang, Peilin Zhong, Simon S. Du, Ruslan Salakhutdinov, Lin F. Yang
2020	J	`jnl`	Planning with Submodular Objective Functions. CoRR Ruosong Wang, Hanrui Zhang, Devendra Singh Chaplot, Denis Garagic, Ruslan Salakhutdinov
2020	A*	`conf`	Preference-based Reinforcement Learning with Finite-Time Guarantees. NeurIPS Yichong Xu, Ruosong Wang, Lin F. Yang, Aarti Singh, Artur Dubrawski
2020	J	`jnl`	Preference-based Reinforcement Learning with Finite-Time Guarantees. CoRR Yichong Xu, Ruosong Wang, Lin F. Yang, Aarti Singh, Artur Dubrawski
2020	J	`jnl`	Provably Efficient Exploration for RL with Unsupervised Learning. CoRR Fei Feng, Ruosong Wang, Wotao Yin, Simon S. Du, Lin F. Yang
2020	A*	`conf`	Provably Efficient Exploration for Reinforcement Learning Using Unsupervised Learning. NeurIPS Fei Feng, Ruosong Wang, Wotao Yin, Simon S. Du, Lin F. Yang
2020	J	`jnl`	Provably Efficient Reinforcement Learning with General Value Function Approximation. CoRR Ruosong Wang, Ruslan Salakhutdinov, Lin F. Yang
2020	A*	`conf`	Reinforcement Learning with General Value Function Approximation: Provably Efficient Approach via Bounded Eluder Dimension. NeurIPS Ruosong Wang, Ruslan Salakhutdinov, Lin F. Yang
2020	A*	`conf`	The Communication Complexity of Optimization. SODA Santosh S. Vempala, Ruosong Wang, David P. Woodruff
2020	A*	`conf`	Tight Bounds for the Subspace Sketch Problem with Applications. SODA Yi Li, Ruosong Wang, David P. Woodruff
2020	J	`jnl`	What are the Statistical Limits of Offline RL with Linear Function Approximation? CoRR Ruosong Wang, Dean P. Foster, Sham M. Kakade
2019	A	`conf`	Classical Algorithms from Quantum and Arthur-Merlin Communication Protocols. ITCS Lijie Chen, Ruosong Wang
2019	J	`jnl`	Continuous Control with Contexts, Provably. CoRR Simon S. Du, Ruosong Wang, Mengdi Wang, Lin F. Yang
2019	A*	`conf`	Dimensionality Reduction for Tukey Regression. ICML Kenneth L. Clarkson, Ruosong Wang, David P. Woodruff
2019	J	`jnl`	Dimensionality Reduction for Tukey Regression. CoRR Kenneth L. Clarkson, Ruosong Wang, David P. Woodruff
2019	A*	`conf`	Efficient Symmetric Norm Regression via Linear Sketching. NeurIPS Zhao Song, Ruosong Wang, Lin F. Yang, Hongyang Zhang, Peilin Zhong
2019	J	`jnl`	Efficient Symmetric Norm Regression via Linear Sketching. CoRR Zhao Song, Ruosong Wang, Lin F. Yang, Hongyang Zhang, Peilin Zhong
2019	J	`jnl`	Enhanced Convolutional Neural Tangent Kernels. CoRR Zhiyuan Li, Ruosong Wang, Dingli Yu, Simon S. Du, Wei Hu, Ruslan Salakhutdinov, Sanjeev Arora
2019	J	`jnl`	Exponential Separations in the Energy Complexity of Leader Election. ACM Trans. Algorithms Yi-Jun Chang, Tsvi Kopelowitz, Seth Pettie, Ruosong Wang, Wei Zhan
2019	A*	`conf`	Fine-Grained Analysis of Optimization and Generalization for Overparameterized Two-Layer Neural Networks. ICML Sanjeev Arora, Simon S. Du, Wei Hu, Zhiyuan Li, Ruosong Wang
2019	J	`jnl`	Fine-Grained Analysis of Optimization and Generalization for Overparameterized Two-Layer Neural Networks. CoRR Sanjeev Arora, Simon S. Du, Wei Hu, Zhiyuan Li, Ruosong Wang
2019	A*	`conf`	Graph Neural Tangent Kernel: Fusing Graph Neural Networks with Graph Kernels. NeurIPS Simon S. Du, Kangcheng Hou, Ruslan Salakhutdinov, Barnabás Póczos, Ruosong Wang, Keyulu Xu
2019	J	`jnl`	Graph Neural Tangent Kernel: Fusing Graph Neural Networks with Graph Kernels. CoRR Simon S. Du, Kangcheng Hou, Barnabás Póczos, Ruslan Salakhutdinov, Ruosong Wang, Keyulu Xu
2019	J	`jnl`	Harnessing the Power of Infinitely Wide Deep Nets on Small-data Tasks. CoRR Sanjeev Arora, Simon S. Du, Zhiyuan Li, Ruslan Salakhutdinov, Ruosong Wang, Dingli Yu
2019	J	`jnl`	Is a Good Representation Sufficient for Sample Efficient Reinforcement Learning? CoRR Simon S. Du, Sham M. Kakade, Ruosong Wang, Lin F. Yang
2019	A*	`conf`	On Exact Computation with an Infinitely Wide Neural Net. NeurIPS Sanjeev Arora, Simon S. Du, Wei Hu, Zhiyuan Li, Ruslan Salakhutdinov, Ruosong Wang
2019	J	`jnl`	On Exact Computation with an Infinitely Wide Neural Net. CoRR Sanjeev Arora, Simon S. Du, Wei Hu, Zhiyuan Li, Ruslan Salakhutdinov, Ruosong Wang
2019	J	`jnl`	Optimism in Reinforcement Learning with Generalized Linear Function Approximation. CoRR Yining Wang, Ruosong Wang, Simon S. Du, Akshay Krishnamurthy
2019	A*	`conf`	Provably Efficient Q-learning with Function Approximation via Distribution Shift Error Checking Oracle. NeurIPS Simon S. Du, Yuping Luo, Ruosong Wang, Hanrui Zhang
2019	J	`jnl`	Provably Efficient Q-learning with Function Approximation via Distribution Shift Error Checking Oracle. CoRR Simon S. Du, Yuping Luo, Ruosong Wang, Hanrui Zhang
2019	J	`jnl`	The Communication Complexity of Optimization. CoRR Santosh S. Vempala, Ruosong Wang, David P. Woodruff
2019	J	`jnl`	Tight Bounds for the Subspace Sketch Problem with Applications. CoRR Yi Li, Ruosong Wang, David P. Woodruff
2019	A*	`conf`	Tight Bounds for ℓp Oblivious Subspace Embeddings. SODA Ruosong Wang, David P. Woodruff
2018	—	`conf`	An Improved Algorithm for Incremental DFS Tree in Undirected Graphs. SWAT Lijie Chen, Ran Duan, Ruosong Wang, Hanrui Zhang, Tianyi Zhang
2018	J	`jnl`	Classical Algorithms from Quantum and Arthur-Merlin Communication Protocols. CoRR Lijie Chen, Ruosong Wang
2018	J	`jnl`	Tight Bounds for 𝓁 CoRR Ruosong Wang, David P. Woodruff
2017	A*	`conf`	Bounded Rationality of Restricted Turing Machines. AAAI Lijie Chen, Pingzhong Tang, Ruosong Wang
2017	A	`conf`	Efficient Near-optimal Algorithms for Barter Exchange. AAMAS Zhipeng Jia, Pingzhong Tang, Ruosong Wang, Hanrui Zhang
2017	A*	`conf`	Exponential separations in the energy complexity of leader election. STOC Yi-Jun Chang, Tsvi Kopelowitz, Seth Pettie, Ruosong Wang, Wei Zhan
2017	A	`conf`	K-Memory Strategies in Repeated Games. AAMAS Lijie Chen, Fangzhen Lin, Pingzhong Tang, Kangning Wang, Ruosong Wang, Shiheng Wang
2017	A*	`conf`	Nearly Optimal Sampling Algorithms for Combinatorial Pure Exploration. COLT Lijie Chen, Anupam Gupta, Jian Li, Mingda Qiao, Ruosong Wang
2017	J	`jnl`	Nearly Optimal Sampling Algorithms for Combinatorial Pure Exploration. CoRR Lijie Chen, Anupam Gupta, Jian Li, Mingda Qiao, Ruosong Wang
2017	A	`conf`	k-Regret Minimizing Set: Efficient Algorithms and Hardness. ICDT Wei Cao, Jian Li, Haitao Wang, Kangning Wang, Ruosong Wang, Raymond Chi-Wing Wong, Wei Zhan
2016	J	`jnl`	How to Elect a Low-energy Leader. CoRR Yi-Jun Chang, Tsvi Kopelowitz, Seth Pettie, Ruosong Wang, Wei Zhan
2016	J	`jnl`	Improved Algorithms for Maintaining DFS Tree in Undirected Graphs. CoRR Lijie Chen, Ran Duan, Ruosong Wang, Hanrui Zhang