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2020 – today
- 2024
[j6]Chi Jin, Qinghua Liu
, Yuanhao Wang, Tiancheng Yu:
V-Learning - A Simple, Efficient, Decentralized Algorithm for Multiagent Reinforcement Learning. Math. Oper. Res. 49(4): 2295-2322 (2024)- [j5]Hui Nie, Tiancheng Yu, Jiangbo Chen, Jiabing Liu, Dongdong Liu, Xiaopeng Yu, Qun Jane Gu, Zhiwei Xu:
A 0.5-8GHz Reconfigurable CMOS RF Receiver Front-End for CR and DPA Applications. IEEE Trans. Circuits Syst. II Express Briefs 71(12): 4819-4823 (2024) - 2023
- [b1]Tiancheng Yu:
Near-Optimal Learning in Sequential Games. MIT, USA, 2023 - [j4]Viet Anh Dang, Ning Gao, Tiancheng Yu:
Climate Policy Risk and Corporate Financial Decisions: Evidence from the NOx Budget Trading Program. Manag. Sci. 69(12): 7517-7539 (2023) - [c14]Ying Feng, Tiancheng Yu:
Modeling of Shape Memory Alloy Artificial Wrist Joint via Modified Prandtl-Ishlinskii Hysteresis Model. ICARM 2023: 1125-1130 - [c13]Ying Feng, Tiancheng Yu:
Tracking Control of Shape Memory Alloy Artificial Wrist Joint Based on Generalized Prandtl-Ishlinskii Inverse Model. ICDL 2023: 164-169 - [c12]Mingyang Liu, Asuman E. Ozdaglar, Tiancheng Yu, Kaiqing Zhang:
The Power of Regularization in Solving Extensive-Form Games. ICLR 2023 - 2022
- [j3]Youqiang Ding, Xiantao He, Li Yang, Dongxing Zhang, Tao Cui, Yuhuan Li, Xiangjun Zhong, Chunji Xie, Zhaohui Du, Tiancheng Yu:
Low-cost turn compensation control system for conserving seeds and increasing yields from maize precision planters. Comput. Electron. Agric. 199: 107118 (2022) - [c11]Yu Bai, Chi Jin, Song Mei, Tiancheng Yu:
Near-Optimal Learning of Extensive-Form Games with Imperfect Information. ICML 2022: 1337-1382 - [c10]Chi Jin, Qinghua Liu, Tiancheng Yu:
The Power of Exploiter: Provable Multi-Agent RL in Large State Spaces. ICML 2022: 10251-10279 - [c9]Yu Bai, Chi Jin, Song Mei, Ziang Song, Tiancheng Yu:
Efficient Phi-Regret Minimization in Extensive-Form Games via Online Mirror Descent. NeurIPS 2022 - [i12]Yu Bai, Chi Jin, Song Mei, Tiancheng Yu:
Near-Optimal Learning of Extensive-Form Games with Imperfect Information. CoRR abs/2202.01752 (2022) - [i11]Yu Bai, Chi Jin, Song Mei, Ziang Song, Tiancheng Yu:
Efficient Φ-Regret Minimization in Extensive-Form Games via Online Mirror Descent. CoRR abs/2205.15294 (2022) - [i10]Mingyang Liu, Asuman E. Ozdaglar, Tiancheng Yu, Kaiqing Zhang:
The Power of Regularization in Solving Extensive-Form Games. CoRR abs/2206.09495 (2022) - 2021
- [j2]Chunji Xie, Dongxing Zhang, Li Yang, Tao Cui, Tiancheng Yu, Decheng Wang, Tianpu Xiao:
Experimental analysis on the variation law of sensor monitoring accuracy under different seeding speed and seeding spacing. Comput. Electron. Agric. 189: 106369 (2021) - [c8]Qinghua Liu, Tiancheng Yu, Yu Bai, Chi Jin:
A Sharp Analysis of Model-based Reinforcement Learning with Self-Play. ICML 2021: 7001-7010 - [c7]Yi Tian, Yuanhao Wang, Tiancheng Yu, Suvrit Sra:
Online Learning in Unknown Markov Games. ICML 2021: 10279-10288 - [c6]Tiancheng Yu, Yi Tian, Jingzhao Zhang, Suvrit Sra:
Provably Efficient Algorithms for Multi-Objective Competitive RL. ICML 2021: 12167-12176 - [i9]Tiancheng Yu, Yi Tian, Jingzhao Zhang, Suvrit Sra:
Provably Efficient Algorithms for Multi-Objective Competitive RL. CoRR abs/2102.03192 (2021) - [i8]Chi Jin, Qinghua Liu, Tiancheng Yu:
The Power of Exploiter: Provable Multi-Agent RL in Large State Spaces. CoRR abs/2106.03352 (2021) - [i7]Chi Jin, Qinghua Liu, Yuanhao Wang, Tiancheng Yu:
V-Learning - A Simple, Efficient, Decentralized Algorithm for Multiagent RL. CoRR abs/2110.14555 (2021) - 2020
- [c5]Chi Jin, Tiancheng Jin, Haipeng Luo, Suvrit Sra, Tiancheng Yu:
Learning Adversarial Markov Decision Processes with Bandit Feedback and Unknown Transition. ICML 2020: 4860-4869 - [c4]Chi Jin, Akshay Krishnamurthy, Max Simchowitz, Tiancheng Yu:
Reward-Free Exploration for Reinforcement Learning. ICML 2020: 4870-4879 - [c3]Yu Bai, Chi Jin, Tiancheng Yu:
Near-Optimal Reinforcement Learning with Self-Play. NeurIPS 2020 - [i6]Chi Jin, Akshay Krishnamurthy, Max Simchowitz, Tiancheng Yu:
Reward-Free Exploration for Reinforcement Learning. CoRR abs/2002.02794 (2020) - [i5]Chi-Ning Chou, Juspreet Singh Sandhu, Mien Brabeeba Wang, Tiancheng Yu:
A General Framework for Analyzing Stochastic Dynamics in Learning Algorithms. CoRR abs/2006.06171 (2020) - [i4]Yu Bai, Chi Jin, Tiancheng Yu:
Near-Optimal Reinforcement Learning with Self-Play. CoRR abs/2006.12007 (2020) - [i3]Qinghua Liu, Tiancheng Yu, Yu Bai, Chi Jin:
A Sharp Analysis of Model-based Reinforcement Learning with Self-Play. CoRR abs/2010.01604 (2020) - [i2]Yi Tian, Yuanhao Wang, Tiancheng Yu, Suvrit Sra:
Provably Efficient Online Agnostic Learning in Markov Games. CoRR abs/2010.15020 (2020)
2010 – 2019
- 2018
- [j1]Tiancheng Yu, Yuan Shen:
Asymptotic Performance Analysis for Landmark Learning in Indoor Localization. IEEE Commun. Lett. 22(4): 740-743 (2018) - [c2]Chengzhi Mao, Kangbo Lin, Tiancheng Yu, Yuan Shen:
A Probabilistic Learning Approach to UWB Ranging Error Mitigation. GLOBECOM 2018: 1-6 - [c1]Yanjun Han, Jiantao Jiao, Chuan-Zheng Lee, Tsachy Weissman, Yihong Wu, Tiancheng Yu:
Entropy Rate Estimation for Markov Chains with Large State Space. NeurIPS 2018: 9803-9814 - [i1]Yanjun Han, Jiantao Jiao, Chuan-Zheng Lee, Tsachy Weissman, Yihong Wu, Tiancheng Yu:
Entropy Rate Estimation for Markov Chains with Large State Space. CoRR abs/1802.07889 (2018)
Coauthor Index
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