Tianhao Wang - RankMe

24 papers A* 11A 2Journal 11

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	Can Neural Networks Achieve Optimal Computational-statistical Tradeoff? An Analysis on Single-Index Model. ICLR Siyu Chen, Beining Wu, Miao Lu, Zhuoran Yang, Tianhao Wang
2025	J	`jnl`	Taming Polysemanticity in LLMs: Provable Feature Recovery via Sparse Autoencoders. CoRR Siyu Chen, Heejune Sheen, Xuyuan Xiong, Tianhao Wang, Zhuoran Yang
2024	J	`jnl`	Implicit Regularization of Gradient Flow on One-Layer Softmax Attention. CoRR Heejune Sheen, Siyu Chen, Tianhao Wang, Harrison H. Zhou
2024	A*	`conf`	Training Dynamics of Multi-Head Softmax Attention for In-Context Learning: Emergence, Convergence, and Optimality (extended abstract). COLT Siyu Chen, Heejune Sheen, Tianhao Wang, Zhuoran Yang
2024	J	`jnl`	Training Dynamics of Multi-Head Softmax Attention for In-Context Learning: Emergence, Convergence, and Optimality. CoRR Siyu Chen, Heejune Sheen, Tianhao Wang, Zhuoran Yang
2024	A*	`conf`	Unveiling Induction Heads: Provable Training Dynamics and Feature Learning in Transformers. NeurIPS Siyu Chen, Heejune Sheen, Tianhao Wang, Zhuoran Yang
2024	J	`jnl`	Unveiling Induction Heads: Provable Training Dynamics and Feature Learning in Transformers. CoRR Siyu Chen, Heejune Sheen, Tianhao Wang, Zhuoran Yang
2023	A*	`conf`	Cooperative Multi-Agent Reinforcement Learning: Asynchronous Communication and Linear Function Approximation. ICML Yifei Min, Jiafan He, Tianhao Wang, Quanquan Gu
2023	J	`jnl`	Cooperative Multi-Agent Reinforcement Learning: Asynchronous Communication and Linear Function Approximation. CoRR Yifei Min, Jiafan He, Tianhao Wang, Quanquan Gu
2023	A	`conf`	Finding Regularized Competitive Equilibria of Heterogeneous Agent Macroeconomic Models via Reinforcement Learning. AISTATS Ruitu Xu, Yifei Min, Tianhao Wang, Michael I. Jordan, Zhaoran Wang, Zhuoran Yang
2023	J	`jnl`	Finding Regularized Competitive Equilibria of Heterogeneous Agent Macroeconomic Models with Reinforcement Learning. CoRR Ruitu Xu, Yifei Min, Tianhao Wang, Zhaoran Wang, Michael I. Jordan, Zhuoran Yang
2023	A*	`conf`	Noise-Adaptive Thompson Sampling for Linear Contextual Bandits. NeurIPS Ruitu Xu, Yifei Min, Tianhao Wang
2022	A*	`conf`	A Simple and Provably Efficient Algorithm for Asynchronous Federated Contextual Linear Bandits. NeurIPS Jiafan He, Tianhao Wang, Yifei Min, Quanquan Gu
2022	J	`jnl`	A Simple and Provably Efficient Algorithm for Asynchronous Federated Contextual Linear Bandits. CoRR Jiafan He, Tianhao Wang, Yifei Min, Quanquan Gu
2022	A*	`conf`	Learn to Match with No Regret: Reinforcement Learning in Markov Matching Markets. NeurIPS Yifei Min, Tianhao Wang, Ruitu Xu, Zhaoran Wang, Michael I. Jordan, Zhuoran Yang
2022	J	`jnl`	Learn to Match with No Regret: Reinforcement Learning in Markov Matching Markets. CoRR Yifei Min, Tianhao Wang, Ruitu Xu, Zhaoran Wang, Michael I. Jordan, Zhuoran Yang
2022	A*	`conf`	Learning Stochastic Shortest Path with Linear Function Approximation. ICML Yifei Min, Jiafan He, Tianhao Wang, Quanquan Gu
2021	J	`jnl`	Learning Stochastic Shortest Path with Linear Function Approximation. CoRR Yifei Min, Jiafan He, Tianhao Wang, Quanquan Gu
2021	J	`jnl`	Provably Efficient Reinforcement Learning with Linear Function Approximation Under Adaptivity Constraints. CoRR Tianhao Wang, Dongruo Zhou, Quanquan Gu
2021	A*	`conf`	Provably Efficient Reinforcement Learning with Linear Function Approximation under Adaptivity Constraints. NeurIPS Tianhao Wang, Dongruo Zhou, Quanquan Gu
2021	A*	`conf`	Variance-Aware Off-Policy Evaluation with Linear Function Approximation. NeurIPS Yifei Min, Tianhao Wang, Dongruo Zhou, Quanquan Gu
2021	J	`jnl`	Variance-Aware Off-Policy Evaluation with Linear Function Approximation. CoRR Yifei Min, Tianhao Wang, Dongruo Zhou, Quanquan Gu
2018	A	`conf`	Accelerated Stochastic Mirror Descent: From Continuous-time Dynamics to Discrete-time Algorithms. AISTATS Pan Xu, Tianhao Wang, Quanquan Gu
2018	A*	`conf`	Continuous and Discrete-time Accelerated Stochastic Mirror Descent for Strongly Convex Functions. ICML Pan Xu, Tianhao Wang, Quanquan Gu