Accelerated Stochastic Mirror Descent: From Continuous-time Dynamics to Discrete-time Algorithms. - Pan Xu 002; Tianhao Wang 002; Quanquan Gu (AISTATS, 2018)

Continuous and Discrete-time Accelerated Stochastic Mirror Descent for Strongly Convex Functions. - Pan Xu 002; Tianhao Wang 002; Quanquan Gu (ICML, 2018)

Variance-Aware Off-Policy Evaluation with Linear Function Approximation. - Yifei Min; Tianhao Wang 002; Dongruo Zhou; Quanquan Gu (NeurIPS, 2021)

Provably Efficient Reinforcement Learning with Linear Function Approximation under Adaptivity Constraints. - Tianhao Wang 002; Dongruo Zhou; Quanquan Gu (NeurIPS, 2021)

Learning Stochastic Shortest Path with Linear Function Approximation. - Yifei Min; Jiafan He; Tianhao Wang 002; Quanquan Gu (ICML, 2022)

A Simple and Provably Efficient Algorithm for Asynchronous Federated Contextual Linear Bandits. - Jiafan He; Tianhao Wang 002; Yifei Min; Quanquan Gu (NeurIPS, 2022)

Learn to Match with No Regret: Reinforcement Learning in Markov Matching Markets. - Yifei Min; Tianhao Wang 002; Ruitu Xu; Zhaoran Wang 001; Michael I. Jordan; Zhuoran Yang (NeurIPS, 2022)

Finding Regularized Competitive Equilibria of Heterogeneous Agent Macroeconomic Models via Reinforcement Learning. - Ruitu Xu; Yifei Min; Tianhao Wang 002; Michael I. Jordan; Zhaoran Wang 001; Zhuoran Yang (AISTATS, 2023)

Cooperative Multi-Agent Reinforcement Learning: Asynchronous Communication and Linear Function Approximation. - Yifei Min; Jiafan He; Tianhao Wang 002; Quanquan Gu (ICML, 2023)

Noise-Adaptive Thompson Sampling for Linear Contextual Bandits. - Ruitu Xu; Yifei Min; Tianhao Wang 002 (NeurIPS, 2023)

Finding Regularized Competitive Equilibria of Heterogeneous Agent Macroeconomic Models with Reinforcement Learning. - Ruitu Xu; Yifei Min; Tianhao Wang 002; Zhaoran Wang 001; Michael I. Jordan; Zhuoran Yang (CoRR, 2023)

Training Dynamics of Multi-Head Softmax Attention for In-Context Learning: Emergence, Convergence, and Optimality (extended abstract). - Siyu Chen 001; Heejune Sheen; Tianhao Wang 002; Zhuoran Yang (COLT, 2024)

Unveiling Induction Heads: Provable Training Dynamics and Feature Learning in Transformers. - Siyu Chen 001; Heejune Sheen; Tianhao Wang 002; Zhuoran Yang (NeurIPS, 2024)

Training Dynamics of Multi-Head Softmax Attention for In-Context Learning: Emergence, Convergence, and Optimality. - Siyu Chen 001; Heejune Sheen; Tianhao Wang 002; Zhuoran Yang (CoRR, 2024)

Implicit Regularization of Gradient Flow on One-Layer Softmax Attention. - Heejune Sheen; Siyu Chen 001; Tianhao Wang 002; Harrison H. Zhou (CoRR, 2024)

Can Neural Networks Achieve Optimal Computational-statistical Tradeoff? An Analysis on Single-Index Model. - Siyu Chen 001; Beining Wu; Miao Lu; Zhuoran Yang; Tianhao Wang 002 (ICLR, 2025)

Taming Polysemanticity in LLMs: Provable Feature Recovery via Sparse Autoencoders. - Siyu Chen 001; Heejune Sheen; Xuyuan Xiong; Tianhao Wang 002; Zhuoran Yang (CoRR, 2025)