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Tianhao Wang 0002
Person information
- affiliation: Toyota Technological Institute at Chicago (TTIC), IL, USA
- affiliation (PhD 2024): Yale University, CT, USA
- affiliation (BS 2018): University of Science & Technology of China, Hefei, China
Other persons with the same name
- Tianhao Wang — disambiguation page
- Tianhao Wang 0001
— University of Virginia, VA, USA (and 3 more)
- Tianhao Wang 0003 — The University of Nottingham, Ningbo, China
- Tianhao Wang 0004 — Harbin Institute of Technology, Harbin, China
- Tianhao Wang 0005
- Tianhao Wang 0006 — University of Waterloo, ON, Canada
- Tianhao Wang 0007
- Tianhao Wang 0008 — Communication University of China, School of Information Engineering, Beijing, China
- Tianhao Wang 0009
- Tianhao Wang 0010 — Fudan University, Zhongshan Hospital, Department of General Practice, Shanghai, China
- Tianhao Wang 0011 — Big Data Management Center, Yichang, China
- Tianhao Wang 0012
- Tianhao Wang 0013 — Harvard University, Cambridge, MA, USA
- Tianhao Wang 0014 — Tsinghua University, Department of Engineering Physics / MoE Key Laboratory of Particle and Radiation Imaging, Beijing, China
- Tianhao Wang 0015 — China Three Gorges University, Big Data Research Center, Yichang, China
- Tianhao Wang 0016 — Southeast University, School of Computer Science and Engineering, Nanjing, China
- Tianhao Wang 0017 — Yale University, Department of Statistics and Data Science, New Haven, CT, USA
- Tianhao Wang 0018 — Fuzhou University, MoE Key Laboratory of Spatial Data Mining and Information Sharing, China
- Tianhao Wang 0019 — Sichuan University, College of Electronics and Information Engineering, Chengdu, China
- Tianhao Wang 0020 — State Grid Tianjin Electrical Power Company, Electric Power Research Institute, China
- Tianhao Wang 0021 — Princeton University, NJ, USA
- Tianhao Wang 0022 — Dalian University of Technology, School of Information and Communication Engineering, China
- Tianhao Wang 0023 — Spallation Neutron Source Science Center, Gongguan, China
- Tianhao Wang 0024 — Nanjing University, Department of Computer Science and Technology, State Key Laboratory for Novel Software Technology, China
- Tianhao Wang 0025 — ByteDance
- Tianhao Wang 0026 — University of Texas at Dallas, TX, USA
- Tianhao Wang 0027 — Northeast Forestry University, College of Computer and Control Engineering, Harbin, China (and 1 more)
- Tianhao Wang 0028 — Tongji University, School of Economics and Management, Shanghai, China
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2020 – today
- 2025
- [c13]Siyu Chen, Beining Wu, Miao Lu, Zhuoran Yang, Tianhao Wang:
Can Neural Networks Achieve Optimal Computational-statistical Tradeoff? An Analysis on Single-Index Model. ICLR 2025 - 2024
- [c12]Siyu Chen, Heejune Sheen, Tianhao Wang, Zhuoran Yang:
Training Dynamics of Multi-Head Softmax Attention for In-Context Learning: Emergence, Convergence, and Optimality (extended abstract). COLT 2024: 4573 - [c11]Siyu Chen, Heejune Sheen, Tianhao Wang, Zhuoran Yang:
Unveiling Induction Heads: Provable Training Dynamics and Feature Learning in Transformers. NeurIPS 2024 - [i10]Siyu Chen, Heejune Sheen, Tianhao Wang, Zhuoran Yang:
Training Dynamics of Multi-Head Softmax Attention for In-Context Learning: Emergence, Convergence, and Optimality. CoRR abs/2402.19442 (2024) - [i9]Heejune Sheen, Siyu Chen, Tianhao Wang, Harrison H. Zhou:
Implicit Regularization of Gradient Flow on One-Layer Softmax Attention. CoRR abs/2403.08699 (2024) - [i8]Siyu Chen, Heejune Sheen, Tianhao Wang, Zhuoran Yang:
Unveiling Induction Heads: Provable Training Dynamics and Feature Learning in Transformers. CoRR abs/2409.10559 (2024) - 2023
- [c10]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: 375-407 - [c9]Yifei Min, Jiafan He, Tianhao Wang, Quanquan Gu:
Cooperative Multi-Agent Reinforcement Learning: Asynchronous Communication and Linear Function Approximation. ICML 2023: 24785-24811 - [c8]Ruitu Xu, Yifei Min, Tianhao Wang:
Noise-Adaptive Thompson Sampling for Linear Contextual Bandits. NeurIPS 2023 - [i7]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 abs/2303.04833 (2023) - [i6]Yifei Min, Jiafan He, Tianhao Wang, Quanquan Gu:
Cooperative Multi-Agent Reinforcement Learning: Asynchronous Communication and Linear Function Approximation. CoRR abs/2305.06446 (2023) - 2022
- [c7]Yifei Min, Jiafan He, Tianhao Wang, Quanquan Gu:
Learning Stochastic Shortest Path with Linear Function Approximation. ICML 2022: 15584-15629 - [c6]Jiafan He, Tianhao Wang, Yifei Min, Quanquan Gu:
A Simple and Provably Efficient Algorithm for Asynchronous Federated Contextual Linear Bandits. NeurIPS 2022 - [c5]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 - [i5]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 abs/2203.03684 (2022) - [i4]Jiafan He, Tianhao Wang, Yifei Min, Quanquan Gu:
A Simple and Provably Efficient Algorithm for Asynchronous Federated Contextual Linear Bandits. CoRR abs/2207.03106 (2022) - 2021
- [c4]Yifei Min, Tianhao Wang, Dongruo Zhou
Variance-Aware Off-Policy Evaluation with Linear Function Approximation. NeurIPS 2021: 7598-7610 - [c3]Tianhao Wang, Dongruo Zhou
Provably Efficient Reinforcement Learning with Linear Function Approximation under Adaptivity Constraints. NeurIPS 2021: 13524-13536 - [i3]Tianhao Wang, Dongruo Zhou, Quanquan Gu:
Provably Efficient Reinforcement Learning with Linear Function Approximation Under Adaptivity Constraints. CoRR abs/2101.02195 (2021) - [i2]Yifei Min, Tianhao Wang, Dongruo Zhou, Quanquan Gu:
Variance-Aware Off-Policy Evaluation with Linear Function Approximation. CoRR abs/2106.11960 (2021) - [i1]Yifei Min, Jiafan He, Tianhao Wang, Quanquan Gu:
Learning Stochastic Shortest Path with Linear Function Approximation. CoRR abs/2110.12727 (2021)
2010 – 2019
- 2018
- [c2]Pan Xu, Tianhao Wang, Quanquan Gu:
Accelerated Stochastic Mirror Descent: From Continuous-time Dynamics to Discrete-time Algorithms. AISTATS 2018: 1087-1096 - [c1]Pan Xu, Tianhao Wang, Quanquan Gu:
Continuous and Discrete-time Accelerated Stochastic Mirror Descent for Strongly Convex Functions. ICML 2018: 5488-5497
Coauthor Index
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last updated on 2025-06-12 22:35 CEST by the dblp team
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