Tianhao Wang

According to our database, Tianhao Wang authored at least 12 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Training Dynamics of Multi-Head Softmax Attention for In-Context Learning: Emergence, Convergence, and Optimality.

Siyu Chen, Heejune Sheen, Tianhao Wang, Zhuoran Yang

CoRR, 2024

2023

Finding Regularized Competitive Equilibria of Heterogeneous Agent Macroeconomic Models with Reinforcement Learning.

Ruitu Xu, Yifei Min, Tianhao Wang, Zhaoran Wang, Michael I. Jordan, Zhuoran Yang

CoRR, 2023

Noise-Adaptive Thompson Sampling for Linear Contextual Bandits.

Ruitu Xu, Yifei Min, Tianhao Wang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Cooperative Multi-Agent Reinforcement Learning: Asynchronous Communication and Linear Function Approximation.

Yifei Min, Jiafan He, Tianhao Wang, Quanquan Gu

Proceedings of the International Conference on Machine Learning, 2023

Finding Regularized Competitive Equilibria of Heterogeneous Agent Macroeconomic Models via Reinforcement Learning.

Ruitu Xu, Yifei Min, Tianhao Wang, Michael I. Jordan, Zhaoran Wang, Zhuoran Yang

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Learn to Match with No Regret: Reinforcement Learning in Markov Matching Markets.

Yifei Min, Tianhao Wang, Ruitu Xu, Zhaoran Wang, Michael I. Jordan, Zhuoran Yang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

A Simple and Provably Efficient Algorithm for Asynchronous Federated Contextual Linear Bandits.

Jiafan He, Tianhao Wang, Yifei Min, Quanquan Gu

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Learning Stochastic Shortest Path with Linear Function Approximation.

Yifei Min, Jiafan He, Tianhao Wang, Quanquan Gu

Proceedings of the International Conference on Machine Learning, 2022

2021

Provably Efficient Reinforcement Learning with Linear Function Approximation under Adaptivity Constraints.

Tianhao Wang, Dongruo Zhou, Quanquan Gu

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Variance-Aware Off-Policy Evaluation with Linear Function Approximation.

Yifei Min, Tianhao Wang, Dongruo Zhou, Quanquan Gu

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2018

Continuous and Discrete-time Accelerated Stochastic Mirror Descent for Strongly Convex Functions.

Pan Xu, Tianhao Wang, Quanquan Gu

Proceedings of the 35th International Conference on Machine Learning, 2018

Accelerated Stochastic Mirror Descent: From Continuous-time Dynamics to Discrete-time Algorithms.

Pan Xu, Tianhao Wang, Quanquan Gu

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018