Tianhao Wang

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 18

Top Topics

Reinforcement Learning

Top Venues

Publications

Siyu Chen, Heejune Sheen, Tianhao Wang, Zhuoran Yang
Training Dynamics of Multi-Head Softmax Attention for In-Context Learning: Emergence, Convergence, and Optimality. CoRR (2024)
Ruitu Xu, Yifei Min, Tianhao Wang
Noise-Adaptive Thompson Sampling for Linear Contextual Bandits. NeurIPS (2023)
Ruitu Xu, Yifei Min, Tianhao Wang, Michael I. Jordan, Zhaoran Wang, Zhuoran Yang
Finding Regularized Competitive Equilibria of Heterogeneous Agent Macroeconomic Models via Reinforcement Learning. AISTATS (2023)
Ruitu Xu, Yifei Min, Tianhao Wang, Zhaoran Wang, Michael I. Jordan, Zhuoran Yang
Finding Regularized Competitive Equilibria of Heterogeneous Agent Macroeconomic Models with Reinforcement Learning. CoRR (2023)
Yifei Min, Jiafan He, Tianhao Wang, Quanquan Gu
Cooperative Multi-Agent Reinforcement Learning: Asynchronous Communication and Linear Function Approximation. ICML (2023)
Yifei Min, Jiafan He, Tianhao Wang, Quanquan Gu
Cooperative Multi-Agent Reinforcement Learning: Asynchronous Communication and Linear Function Approximation. CoRR (2023)
Yifei Min, Tianhao Wang, Ruitu Xu, Zhaoran Wang, Michael I. Jordan, Zhuoran Yang
Learn to Match with No Regret: Reinforcement Learning in Markov Matching Markets. CoRR (2022)
Jiafan He, Tianhao Wang, Yifei Min, Quanquan Gu
A Simple and Provably Efficient Algorithm for Asynchronous Federated Contextual Linear Bandits. CoRR (2022)
Yifei Min, Jiafan He, Tianhao Wang, Quanquan Gu
Learning Stochastic Shortest Path with Linear Function Approximation. ICML (2022)
Yifei Min, Tianhao Wang, Ruitu Xu, Zhaoran Wang, Michael I. Jordan, Zhuoran Yang
Learn to Match with No Regret: Reinforcement Learning in Markov Matching Markets. NeurIPS (2022)
Jiafan He, Tianhao Wang, Yifei Min, Quanquan Gu
A Simple and Provably Efficient Algorithm for Asynchronous Federated Contextual Linear Bandits. NeurIPS (2022)
Tianhao Wang, Dongruo Zhou, Quanquan Gu
Provably Efficient Reinforcement Learning with Linear Function Approximation Under Adaptivity Constraints. CoRR (2021)
Yifei Min, Tianhao Wang, Dongruo Zhou, Quanquan Gu
Variance-Aware Off-Policy Evaluation with Linear Function Approximation. NeurIPS (2021)
Yifei Min, Tianhao Wang, Dongruo Zhou, Quanquan Gu
Variance-Aware Off-Policy Evaluation with Linear Function Approximation. CoRR (2021)
Tianhao Wang, Dongruo Zhou, Quanquan Gu
Provably Efficient Reinforcement Learning with Linear Function Approximation under Adaptivity Constraints. NeurIPS (2021)
Yifei Min, Jiafan He, Tianhao Wang, Quanquan Gu
Learning Stochastic Shortest Path with Linear Function Approximation. CoRR (2021)
Pan Xu, Tianhao Wang, Quanquan Gu
Continuous and Discrete-time Accelerated Stochastic Mirror Descent for Strongly Convex Functions. ICML (2018)
Pan Xu, Tianhao Wang, Quanquan Gu
Accelerated Stochastic Mirror Descent: From Continuous-time Dynamics to Discrete-time Algorithms. AISTATS (2018)