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2020 – today
- 2024
[j3]Tiantian Zhang
, Zichuan Lin, Yuxing Wang, Deheng Ye, Qiang Fu, Wei Yang, Xueqian Wang, Bin Liang, Bo Yuan, Xiu Li:
Dynamics-Adaptive Continual Reinforcement Learning via Progressive Contextualization. IEEE Trans. Neural Networks Learn. Syst. 35(10): 14588-14602 (2024)- 2023
- [j2]Tiantian Zhang, Kevin Z. Shen, Zichuan Lin, Bo Yuan, Xueqian Wang, Xiu Li, Deheng Ye:
Replay-enhanced Continual Reinforcement Learning. Trans. Mach. Learn. Res. 2023 (2023) - [j1]Wenzhe Li, Hao Luo, Zichuan Lin, Chongjie Zhang, Zongqing Lu, Deheng Ye:
A Survey on Transformers in Reinforcement Learning. Trans. Mach. Learn. Res. 2023 (2023) - [c11]Zhihui Xie, Zichuan Lin, Deheng Ye, Qiang Fu, Yang Wei, Shuai Li:
Future-conditioned Unsupervised Pretraining for Decision Transformer. ICML 2023: 38187-38203 - [i14]Wenzhe Li, Hao Luo, Zichuan Lin, Chongjie Zhang, Zongqing Lu, Deheng Ye:
A Survey on Transformers in Reinforcement Learning. CoRR abs/2301.03044 (2023) - [i13]Zichuan Lin, Xiapeng Wu, Mingfei Sun, Deheng Ye, Qiang Fu, Wei Yang, Wei Liu:
Sample Dropout: A Simple yet Effective Variance Reduction Technique in Deep Policy Optimization. CoRR abs/2302.02299 (2023) - [i12]Zhihui Xie, Zichuan Lin, Deheng Ye, Qiang Fu, Wei Yang, Shuai Li:
Future-conditioned Unsupervised Pretraining for Decision Transformer. CoRR abs/2305.16683 (2023) - [i11]Tiantian Zhang, Kevin Z. Shen, Zichuan Lin, Bo Yuan, Xueqian Wang, Xiu Li, Deheng Ye:
Replay-enhanced Continual Reinforcement Learning. CoRR abs/2311.11557 (2023) - 2022
- [c10]Zichuan Lin, Junyou Li, Jianing Shi, Deheng Ye, Qiang Fu, Wei Yang:
JueWu-MC: Playing Minecraft with Sample-efficient Hierarchical Reinforcement Learning. IJCAI 2022: 3257-3263 - [i10]Anssi Kanervisto, Stephanie Milani, Karolis Ramanauskas, Nicholay Topin, Zichuan Lin, Junyou Li, Jianing Shi, Deheng Ye, Qiang Fu, Wei Yang, Weijun Hong, Zhongyue Huang, Haicheng Chen, Guangjun Zeng, Yue Lin, Vincent Micheli, Eloi Alonso, François Fleuret, Alexander Nikulin, Yury Belousov, Oleg Svidchenko, Aleksei Shpilman:
MineRL Diamond 2021 Competition: Overview, Results, and Lessons Learned. CoRR abs/2202.10583 (2022) - [i9]Tiantian Zhang, Zichuan Lin, Yuxing Wang, Deheng Ye, Qiang Fu, Wei Yang, Xueqian Wang, Bin Liang, Bo Yuan, Xiu Li:
Dynamics-Adaptive Continual Reinforcement Learning via Progressive Contextualization. CoRR abs/2209.00347 (2022) - [i8]Haibin Zhou, Zichuan Lin, Junyou Li, Deheng Ye, Qiang Fu, Wei Yang:
Revisiting Discrete Soft Actor-Critic. CoRR abs/2209.10081 (2022) - [i7]Zhihui Xie, Zichuan Lin, Junyou Li, Shuai Li, Deheng Ye:
Pretraining in Deep Reinforcement Learning: A Survey. CoRR abs/2211.03959 (2022) - 2021
- [c9]Anssi Kanervisto, Stephanie Milani, Karolis Ramanauskas, Nicholay Topin, Zichuan Lin, Junyou Li, Jianing Shi, Deheng Ye, Qiang Fu, Wei Yang, Weijun Hong, Zhongyue Huang, Haicheng Chen, Guangjun Zeng, Yue Lin, Vincent Micheli, Eloi Alonso, François Fleuret, Alexander Nikulin, Yury Belousov, Oleg Svidchenko, Aleksei Shpilman:
MineRL Diamond 2021 Competition: Overview, Results, and Lessons Learned. NeurIPS (Competition and Demos) 2021: 13-28 - [i6]Zichuan Lin, Jing Huang, Bowen Zhou, Xiaodong He, Tengyu Ma:
Joint System-Wise Optimization for Pipeline Goal-Oriented Dialog System. CoRR abs/2106.04835 (2021) - [i5]Zichuan Lin, Junyou Li, Jianing Shi, Deheng Ye, Qiang Fu, Wei Yang:
JueWu-MC: Playing Minecraft with Sample-efficient Hierarchical Reinforcement Learning. CoRR abs/2112.04907 (2021) - 2020
- [c8]Guangxiang Zhu, Jianhao Wang, Zhizhou Ren, Zichuan Lin, Chongjie Zhang:
Object-Oriented Dynamics Learning through Multi-Level Abstraction. AAAI 2020: 6989-6998 - [c7]Guangxiang Zhu, Zichuan Lin, Guangwen Yang, Chongjie Zhang:
Episodic Reinforcement Learning with Associative Memory. ICLR 2020 - [c6]Zichuan Lin, Garrett Thomas, Guangwen Yang, Tengyu Ma:
Model-based Adversarial Meta-Reinforcement Learning. NeurIPS 2020 - [c5]Zichuan Lin, Derek Yang, Li Zhao, Tao Qin, Guangwen Yang, Tie-Yan Liu:
RD$^2$: Reward Decomposition with Representation Decomposition. NeurIPS 2020 - [i4]Zichuan Lin, Garrett Thomas, Guangwen Yang, Tengyu Ma:
Model-based Adversarial Meta-Reinforcement Learning. CoRR abs/2006.08875 (2020)
2010 – 2019
- 2019
- [c4]Zichuan Lin, Li Zhao, Jiang Bian, Tao Qin, Guangwen Yang:
Unified Policy Optimization for Robust Reinforcement Learning. ACML 2019: 395-410 - [c3]Derek Yang, Li Zhao, Zichuan Lin, Tao Qin, Jiang Bian, Tie-Yan Liu:
Fully Parameterized Quantile Function for Distributional Reinforcement Learning. NeurIPS 2019: 6190-6199 - [c2]Zichuan Lin, Li Zhao, Derek Yang, Tao Qin, Tie-Yan Liu, Guangwen Yang:
Distributional Reward Decomposition for Reinforcement Learning. NeurIPS 2019: 6212-6221 - [i3]Derek Yang, Li Zhao, Zichuan Lin, Tao Qin, Jiang Bian, Tie-Yan Liu:
Fully Parameterized Quantile Function for Distributional Reinforcement Learning. CoRR abs/1911.02140 (2019) - [i2]Zichuan Lin, Li Zhao, Derek Yang, Tao Qin, Guangwen Yang, Tie-Yan Liu:
Distributional Reward Decomposition for Reinforcement Learning. CoRR abs/1911.02166 (2019) - 2018
- [c1]Zichuan Lin, Tianqi Zhao, Guangwen Yang, Lintao Zhang:
Episodic Memory Deep Q-Networks. IJCAI 2018: 2433-2439 - [i1]Zichuan Lin, Tianqi Zhao, Guangwen Yang, Lintao Zhang:
Episodic Memory Deep Q-Networks. CoRR abs/1805.07603 (2018)
Coauthor Index
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