Ruosong Wang

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 76

Top Topics

Function Approximation

Markov Decision Process

Reinforcement Learning

Top Venues

Publications

Ally Yalei Du, Lin F. Yang, Ruosong Wang
Misspecified Q-Learning with Sparse Linear Function Approximation: Tight Bounds on Approximation Error. CoRR (2024)
Runlong Zhou, Ruosong Wang, Simon Shaolei Du
Horizon-Free and Variance-Dependent Reinforcement Learning for Latent Markov Decision Processes. ICML (2023)
Yan Dai, Ruosong Wang, Simon Shaolei Du
Variance-Aware Sparse Linear Bandits. ICLR (2023)
Hanlin Zhu, Ruosong Wang, Jason D. Lee
Provably Efficient Reinforcement Learning via Surprise Bound. AISTATS (2023)
Hanlin Zhu, Ruosong Wang, Jason D. Lee
Provably Efficient Reinforcement Learning via Surprise Bound. CoRR (2023)
Runlong Zhou, Ruosong Wang, Simon S. Du
Horizon-Free Reinforcement Learning for Latent Markov Decision Processes. CoRR (2022)
Ruosong Wang, David P. Woodruff
Oblivious Subspace Embeddings. ACM Trans. Algorithms 18 (1) (2022)
Yan Dai, Ruosong Wang, Simon S. Du
Variance-Aware Sparse Linear Bandits. CoRR (2022)
Yuanzhi Li, Ruosong Wang, Lin F. Yang
Settling the Horizon-Dependence of Sample Complexity in Reinforcement Learning. FOCS (2022)
Yuanhao Wang, Ruosong Wang, Sham M. Kakade
An Exponential Lower Bound for Linearly-Realizable MDPs with Constant Suboptimality Gap. CoRR (2021)
Yuanzhi Li, Ruosong Wang, Lin F. Yang
Settling the Horizon-Dependence of Sample Complexity in Reinforcement Learning. CoRR (2021)
Ruosong Wang, Yifan Wu, Ruslan Salakhutdinov, Sham M. Kakade
Instabilities of Offline RL with Pre-Trained Neural Representation. ICML (2021)
Simon S. Du, Sham M. Kakade, Jason D. Lee, Shachar Lovett, Gaurav Mahajan, Wen Sun, Ruosong Wang
Bilinear Classes: A Structural Framework for Provable Generalization in RL. ICML (2021)
Simon S. Du, Sham M. Kakade, Jason D. Lee, Shachar Lovett, Gaurav Mahajan, Wen Sun, Ruosong Wang
Bilinear Classes: A Structural Framework for Provable Generalization in RL. CoRR (2021)
Dingwen Kong, Ruslan Salakhutdinov, Ruosong Wang, Lin F. Yang
Online Sub-Sampling for Reinforcement Learning with General Function Approximation. CoRR (2021)
Ruosong Wang, Yifan Wu, Ruslan Salakhutdinov, Sham M. Kakade
Instabilities of Offline RL with Pre-Trained Neural Representation. CoRR (2021)
Yuanzhi Li, Ruosong Wang, Lin F. Yang
Settling the Horizon-Dependence of Sample Complexity in Reinforcement Learning. FOCS (2021)
Yuanhao Wang, Ruosong Wang, Sham M. Kakade
An Exponential Lower Bound for Linearly Realizable MDP with Constant Suboptimality Gap. NeurIPS (2021)
Yi Li, Ruosong Wang, David P. Woodruff
Tight Bounds for the Subspace Sketch Problem with Applications. SIAM J. Comput. 50 (4) (2021)
Ruosong Wang, Dean P. Foster, Sham M. Kakade
What are the Statistical Limits of Offline RL with Linear Function Approximation? ICLR (2021)
Yining Wang, Ruosong Wang, Simon Shaolei Du, Akshay Krishnamurthy
Optimism in Reinforcement Learning with Generalized Linear Function Approximation. ICLR (2021)
Fei Feng, Ruosong Wang, Wotao Yin, Simon S. Du, Lin F. Yang
Provably Efficient Exploration for Reinforcement Learning Using Unsupervised Learning. NeurIPS (2020)
Ruosong Wang, Dean P. Foster, Sham M. Kakade
What are the Statistical Limits of Offline RL with Linear Function Approximation? CoRR (2020)
Simon S. Du, Jason D. Lee, Gaurav Mahajan, Ruosong Wang
Agnostic $Q$-learning with Function Approximation in Deterministic Systems: Near-Optimal Bounds on Approximation Error and Sample Complexity. NeurIPS (2020)
Ruosong Wang, Russ R. Salakhutdinov, Lin F. Yang
Reinforcement Learning with General Value Function Approximation: Provably Efficient Approach via Bounded Eluder Dimension. NeurIPS (2020)
Yichong Xu, Ruosong Wang, Lin F. Yang, Aarti Singh, Artur Dubrawski
Preference-based Reinforcement Learning with Finite-Time Guarantees. NeurIPS (2020)
Ruosong Wang, Simon S. Du, Lin F. Yang, Russ R. Salakhutdinov
On Reward-Free Reinforcement Learning with Linear Function Approximation. NeurIPS (2020)
Yi Li, Ruosong Wang, Lin Yang, Hanrui Zhang
Nearly Linear Row Sampling Algorithm for Quantile Regression. CoRR (2020)
Yichong Xu, Ruosong Wang, Lin F. Yang, Aarti Singh, Artur Dubrawski
Preference-based Reinforcement Learning with Finite-Time Guarantees. CoRR (2020)
Ruosong Wang, Ruslan Salakhutdinov, Lin F. Yang
Provably Efficient Reinforcement Learning with General Value Function Approximation. CoRR (2020)
Ruosong Wang, Hanrui Zhang, Devendra Singh Chaplot, Denis Garagic, Ruslan Salakhutdinov
Planning with Submodular Objective Functions. CoRR (2020)
Santosh S. Vempala, Ruosong Wang, David P. Woodruff
The Communication Complexity of Optimization. SODA (2020)
Simon S. Du, Jason D. Lee, Gaurav Mahajan, Ruosong Wang
Agnostic Q-learning with Function Approximation in Deterministic Systems: Tight Bounds on Approximation Error and Sample Complexity. CoRR (2020)
Sanjeev Arora, Simon S. Du, Zhiyuan Li, Ruslan Salakhutdinov, Ruosong Wang, Dingli Yu
Harnessing the Power of Infinitely Wide Deep Nets on Small-data Tasks. ICLR (2020)
Simon S. Du, Sham M. Kakade, Ruosong Wang, Lin F. Yang
Is a Good Representation Sufficient for Sample Efficient Reinforcement Learning? ICLR (2020)
Ruosong Wang, Simon S. Du, Lin F. Yang, Sham M. Kakade
Is Long Horizon RL More Difficult Than Short Horizon RL? NeurIPS (2020)
Ruosong Wang, Peilin Zhong, Simon S. Du, Russ R. Salakhutdinov, Lin F. Yang
Planning with General Objective Functions: Going Beyond Total Rewards. NeurIPS (2020)
Yi Li, Ruosong Wang, Lin Yang, Hanrui Zhang
Nearly Linear Row Sampling Algorithm for Quantile Regression. ICML (2020)
Ruosong Wang, Simon S. Du, Lin F. Yang, Ruslan Salakhutdinov
On Reward-Free Reinforcement Learning with Linear Function Approximation. CoRR (2020)
Yi Li, Ruosong Wang, David P. Woodruff
Tight Bounds for the Subspace Sketch Problem with Applications. SODA (2020)
Fei Feng, Ruosong Wang, Wotao Yin, Simon S. Du, Lin F. Yang
Provably Efficient Exploration for RL with Unsupervised Learning. CoRR (2020)
Ruosong Wang, Simon S. Du, Lin F. Yang, Sham M. Kakade
Is Long Horizon Reinforcement Learning More Difficult Than Short Horizon Reinforcement Learning? CoRR (2020)
Simon S. Du, Ruosong Wang, Mengdi Wang, Lin F. Yang
Continuous Control with Contexts, Provably. CoRR (2019)
Simon S. Du, Kangcheng Hou, Ruslan Salakhutdinov, Barnabás Póczos, Ruosong Wang, Keyulu Xu
Graph Neural Tangent Kernel: Fusing Graph Neural Networks with Graph Kernels. NeurIPS (2019)
Kenneth L. Clarkson, Ruosong Wang, David P. Woodruff
Dimensionality Reduction for Tukey Regression. CoRR (2019)
Simon S. Du, Yuping Luo, Ruosong Wang, Hanrui Zhang
Provably Efficient Q-learning with Function Approximation via Distribution Shift Error Checking Oracle. CoRR (2019)
Sanjeev Arora, Simon S. Du, Wei Hu, Zhiyuan Li, Ruslan Salakhutdinov, Ruosong Wang
On Exact Computation with an Infinitely Wide Neural Net. CoRR (2019)
Ruosong Wang, David P. Woodruff
Tight Bounds for ℓp Oblivious Subspace Embeddings. SODA (2019)
Yining Wang, Ruosong Wang, Simon S. Du, Akshay Krishnamurthy
Optimism in Reinforcement Learning with Generalized Linear Function Approximation. CoRR (2019)
Santosh S. Vempala, Ruosong Wang, David P. Woodruff
The Communication Complexity of Optimization. CoRR (2019)
Zhao Song, Ruosong Wang, Lin F. Yang, Hongyang Zhang, Peilin Zhong
Efficient Symmetric Norm Regression via Linear Sketching. CoRR (2019)
Simon S. Du, Yuping Luo, Ruosong Wang, Hanrui Zhang
Provably Efficient Q-learning with Function Approximation via Distribution Shift Error Checking Oracle. NeurIPS (2019)
Yi-Jun Chang, Tsvi Kopelowitz, Seth Pettie, Ruosong Wang, Wei Zhan
Exponential Separations in the Energy Complexity of Leader Election. ACM Trans. Algorithms 15 (4) (2019)
Simon S. Du, Kangcheng Hou, Barnabás Póczos, Ruslan Salakhutdinov, Ruosong Wang, Keyulu Xu
Graph Neural Tangent Kernel: Fusing Graph Neural Networks with Graph Kernels. CoRR (2019)
Sanjeev Arora, Simon S. Du, Wei Hu, Zhiyuan Li, Ruosong Wang
Fine-Grained Analysis of Optimization and Generalization for Overparameterized Two-Layer Neural Networks. ICML (2019)
Zhiyuan Li, Ruosong Wang, Dingli Yu, Simon S. Du, Wei Hu, Ruslan Salakhutdinov, Sanjeev Arora
Enhanced Convolutional Neural Tangent Kernels. CoRR (2019)
Kenneth L. Clarkson, Ruosong Wang, David P. Woodruff
Dimensionality Reduction for Tukey Regression. ICML (2019)
Sanjeev Arora, Simon S. Du, Wei Hu, Zhiyuan Li, Ruosong Wang
Fine-Grained Analysis of Optimization and Generalization for Overparameterized Two-Layer Neural Networks. CoRR (2019)
Zhao Song, Ruosong Wang, Lin F. Yang, Hongyang Zhang, Peilin Zhong
Efficient Symmetric Norm Regression via Linear Sketching. NeurIPS (2019)
Sanjeev Arora, Simon S. Du, Zhiyuan Li, Ruslan Salakhutdinov, Ruosong Wang, Dingli Yu
Harnessing the Power of Infinitely Wide Deep Nets on Small-data Tasks. CoRR (2019)
Sanjeev Arora, Simon S. Du, Wei Hu, Zhiyuan Li, Ruslan Salakhutdinov, Ruosong Wang
On Exact Computation with an Infinitely Wide Neural Net. NeurIPS (2019)
Yi Li, Ruosong Wang, David P. Woodruff
Tight Bounds for the Subspace Sketch Problem with Applications. CoRR (2019)
Lijie Chen, Ruosong Wang
Classical Algorithms from Quantum and Arthur-Merlin Communication Protocols. ITCS (2019)
Simon S. Du, Sham M. Kakade, Ruosong Wang, Lin F. Yang
Is a Good Representation Sufficient for Sample Efficient Reinforcement Learning? CoRR (2019)
Ruosong Wang, David P. Woodruff
Oblivious Subspace Embeddings. CoRR (2018)
Lijie Chen, Ran Duan, Ruosong Wang, Hanrui Zhang, Tianyi Zhang
An Improved Algorithm for Incremental DFS Tree in Undirected Graphs. SWAT (2018)
Lijie Chen, Ruosong Wang
Classical Algorithms from Quantum and Arthur-Merlin Communication Protocols. CoRR (2018)
Zhipeng Jia, Pingzhong Tang, Ruosong Wang, Hanrui Zhang
Efficient Near-optimal Algorithms for Barter Exchange. AAMAS (2017)
Yi-Jun Chang, Tsvi Kopelowitz, Seth Pettie, Ruosong Wang, Wei Zhan
Exponential separations in the energy complexity of leader election. STOC (2017)
Lijie Chen, Anupam Gupta, Jian Li, Mingda Qiao, Ruosong Wang
Nearly Optimal Sampling Algorithms for Combinatorial Pure Exploration. COLT (2017)
Lijie Chen, Anupam Gupta, Jian Li, Mingda Qiao, Ruosong Wang
Nearly Optimal Sampling Algorithms for Combinatorial Pure Exploration. CoRR (2017)
Lijie Chen, Pingzhong Tang, Ruosong Wang
Bounded Rationality of Restricted Turing Machines. AAAI (2017)
Lijie Chen, Fangzhen Lin, Pingzhong Tang, Kangning Wang, Ruosong Wang, Shiheng Wang
K-Memory Strategies in Repeated Games. AAMAS (2017)
Wei Cao, Jian Li, Haitao Wang, Kangning Wang, Ruosong Wang, Raymond Chi-Wing Wong, Wei Zhan
k-Regret Minimizing Set: Efficient Algorithms and Hardness. ICDT (2017)
Yi-Jun Chang, Tsvi Kopelowitz, Seth Pettie, Ruosong Wang, Wei Zhan
How to Elect a Low-energy Leader. CoRR (2016)
Lijie Chen, Ran Duan, Ruosong Wang, Hanrui Zhang
Improved Algorithms for Maintaining DFS Tree in Undirected Graphs. CoRR (2016)