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2020 – today
- 2024
[c26]Xi Zeng, Xiaotian Hao, Hongyao Tang, Zhentao Tang, Shaoqing Jiao, Dazhi Lu, Jiajie Peng:
Designing Biological Sequences without Prior Knowledge Using Evolutionary Reinforcement Learning. AAAI 2024: 383-391- [c25]Xiaotian Hao, Jianye Hao, Chenjun Xiao, Kai Li, Dong Li, Yan Zheng:
Multiagent Gumbel MuZero: Efficient Planning in Combinatorial Action Spaces. AAAI 2024: 12304-12312 - [c24]Jizhou Wu, Jianye Hao, Tianpei Yang, Xiaotian Hao, Yan Zheng, Weixun Wang, Matthew E. Taylor:
PORTAL: Automatic Curricula Generation for Multiagent Reinforcement Learning. AAAI 2024: 15934-15942 - 2023
- [j5]Tianpei Yang, Weixun Wang, Jianye Hao, Matthew E. Taylor, Yong Liu, Xiaotian Hao, Yujing Hu, Yingfeng Chen, Changjie Fan, Chunxu Ren, Ye Huang, Jiangcheng Zhu, Yang Gao:
ASN: action semantics network for multiagent reinforcement learning. Auton. Agents Multi Agent Syst. 37(2): 45 (2023) - [c23]Jizhou Wu, Tianpei Yang, Xiaotian Hao, Jianye Hao, Yan Zheng, Weixun Wang, Matthew E. Taylor:
PORTAL: Automatic Curricula Generation for Multiagent Reinforcement Learning. AAMAS 2023: 2460-2462 - [c22]Hebin Liang
, Zibin Dong, Yi Ma, Xiaotian Hao, Yan Zheng, Jianye Hao:
A Hierarchical Imitation Learning-based Decision Framework for Autonomous Driving. CIKM 2023: 4695-4701 - [c21]Jingqing Ruan, Xiaotian Hao, Dong Li, Hangyu Mao:
Learning to Collaborate by Grouping: A Consensus-Oriented Strategy for Multi-Agent Reinforcement Learning. ECAI 2023: 2010-2017 - [c20]Jianye Hao, Xiaotian Hao, Hangyu Mao, Weixun Wang, Yaodong Yang, Dong Li, Yan Zheng, Zhen Wang:
Boosting Multiagent Reinforcement Learning via Permutation Invariant and Permutation Equivariant Networks. ICLR 2023 - [i10]Jingqing Ruan, Xiaotian Hao, Dong Li, Hangyu Mao:
Learning to Collaborate by Grouping: a Consensus-oriented Strategy for Multi-agent Reinforcement Learning. CoRR abs/2307.15530 (2023) - 2022
- [j4]Ji Cheng, Da Yan, Wenwen Qu, Xiaotian Hao, Cheng Long, Wilfred Ng, Xiaoling Wang:
Mining Order-preserving Submatrices under Data Uncertainty: A Possible-world Approach and Efficient Approximation Methods. ACM Trans. Database Syst. 47(2): 7:1-7:57 (2022) - [c19]Pengyi Li, Hongyao Tang, Tianpei Yang, Xiaotian Hao, Tong Sang, Yan Zheng, Jianye Hao, Matthew E. Taylor, Wenyuan Tao, Zhen Wang:
PMIC: Improving Multi-Agent Reinforcement Learning with Progressive Mutual Information Collaboration. ICML 2022: 12979-12997 - [c18]Yaodong Yang, Guangyong Chen, Weixun Wang, Xiaotian Hao, Jianye Hao, Pheng-Ann Heng:
Transformer-based Working Memory for Multiagent Reinforcement Learning with Action Parsing. NeurIPS 2022 - [i9]Xiaotian Hao, Weixun Wang, Hangyu Mao, Yaodong Yang, Dong Li, Yan Zheng, Zhen Wang, Jianye Hao:
API: Boosting Multi-Agent Reinforcement Learning via Agent-Permutation-Invariant Networks. CoRR abs/2203.05285 (2022) - [i8]Pengyi Li, Hongyao Tang, Tianpei Yang, Xiaotian Hao, Tong Sang, Yan Zheng, Jianye Hao, Matthew E. Taylor, Zhen Wang:
PMIC: Improving Multi-Agent Reinforcement Learning with Progressive Mutual Information Collaboration. CoRR abs/2203.08553 (2022) - 2021
- [c17]Hangyu Mao, Chao Wang, Xiaotian Hao, Yihuan Mao, Yiming Lu, Chengjie Wu, Jianye Hao, Dong Li, Pingzhong Tang:
SEIHAI: A Sample-Efficient Hierarchical AI for the MineRL Competition. DAI 2021: 38-51 - [c16]Yi Ma, Xiaotian Hao, Jianye Hao, Jiawen Lu, Xing Liu, Xialiang Tong, Mingxuan Yuan, Zhigang Li, Jie Tang, Zhaopeng Meng:
A Hierarchical Reinforcement Learning Based Optimization Framework for Large-scale Dynamic Pickup and Delivery Problems. NeurIPS 2021: 23609-23620 - [i7]William Hebgen Guss, Stephanie Milani, Nicholay Topin, Brandon Houghton, Sharada P. Mohanty, Andrew Melnik, Augustin Harter, Benoit Buschmaas, Bjarne Jaster, Christoph Berganski, Dennis Heitkamp, Marko Henning, Helge J. Ritter, Chengjie Wu, Xiaotian Hao, Yiming Lu, Hangyu Mao, Yihuan Mao, Chao Wang, Michal Opanowicz, Anssi Kanervisto, Yanick Schraner, Christian Scheller, Xiren Zhou, Lu Liu, Daichi Nishio, Toi Tsuneda, Karolis Ramanauskas, Gabija Juceviciute:
Towards robust and domain agnostic reinforcement learning competitions. CoRR abs/2106.03748 (2021) - [i6]Hangyu Mao, Chao Wang, Xiaotian Hao, Yihuan Mao, Yiming Lu, Chengjie Wu, Jianye Hao, Dong Li, Pingzhong Tang:
SEIHAI: A Sample-efficient Hierarchical AI for the MineRL Competition. CoRR abs/2111.08857 (2021) - 2020
- [j3]Leilei Liu, Xianglei Zhu, Yi Ma, Haiyin Piao, Yaodong Yang, Xiaotian Hao, Yue Fu, Li Wang, Jiajie Peng:
Combining sequence and network information to enhance protein-protein interaction prediction. BMC Bioinform. 21-S(16): 537 (2020) - [j2]Yan Zheng, Jianye Hao, Zongzhang Zhang, Zhao-Peng Meng, Xiaotian Hao:
Efficient Multiagent Policy Optimization Based on Weighted Estimators in Stochastic Cooperative Environments. J. Comput. Sci. Technol. 35(2): 268-280 (2020) - [c15]Weixun Wang, Tianpei Yang, Yong Liu, Jianye Hao, Xiaotian Hao, Yujing Hu, Yingfeng Chen, Changjie Fan, Yang Gao:
From Few to More: Large-Scale Dynamic Multiagent Curriculum Learning. AAAI 2020: 7293-7300 - [c14]Hanchao Wang, Hongyao Tang, Jianye Hao, Xiaotian Hao, Yue Fu, Yi Ma:
Large Scale Deep Reinforcement Learning in War-games. BIBM 2020: 1693-1699 - [c13]Weixun Wang, Tianpei Yang, Yong Liu, Jianye Hao, Xiaotian Hao, Yujing Hu, Yingfeng Chen, Changjie Fan, Yang Gao:
Action Semantics Network: Considering the Effects of Actions in Multiagent Systems. ICLR 2020 - [c12]Xiaotian Hao, Zhaoqing Peng, Yi Ma, Guan Wang, Junqi Jin, Jianye Hao, Shan Chen, Rongquan Bai, Mingzhou Xie, Miao Xu, Zhenzhe Zheng, Chuan Yu, Han Li, Jian Xu, Kun Gai:
Dynamic Knapsack Optimization Towards Efficient Multi-Channel Sequential Advertising. ICML 2020: 4060-4070 - [c11]Xiaotian Hao, Junqi Jin, Jianye Hao, Jin Li, Weixun Wang, Yi Ma, Zhenzhe Zheng, Han Li, Jian Xu, Kun Gai:
Learning to Accelerate Heuristic Searching for Large-Scale Maximum Weighted b-Matching Problems in Online Advertising. IJCAI 2020: 3437-3443 - [c10]William Hebgen Guss, Stephanie Milani, Nicholay Topin, Brandon Houghton, Sharada P. Mohanty, Andrew Melnik, Augustin Harter, Benoit Buschmaas, Bjarne Jaster, Christoph Berganski, Dennis Heitkamp, Marko Henning, Helge J. Ritter, Chengjie Wu, Xiaotian Hao, Yiming Lu, Hangyu Mao, Yihuan Mao, Chao Wang, Michal Opanowicz, Anssi Kanervisto, Yanick Schraner, Christian Scheller, Xiren Zhou, Lu Liu, Daichi Nishio, Toi Tsuneda, Karolis Ramanauskas, Gabija Juceviciute:
Towards robust and domain agnostic reinforcement learning competitions: MineRL 2020. NeurIPS (Competition and Demos) 2020: 233-252 - [i5]Xiaotian Hao, Junqi Jin, Jianye Hao, Jin Li, Weixun Wang, Yi Ma, Zhenzhe Zheng, Han Li, Jian Xu, Kun Gai:
Learning to Accelerate Heuristic Searching for Large-Scale Maximum Weighted b-Matching Problems in Online Advertising. CoRR abs/2005.04355 (2020) - [i4]Xiaotian Hao, Zhaoqing Peng, Yi Ma, Guan Wang, Junqi Jin, Jianye Hao, Shan Chen, Rongquan Bai, Mingzhou Xie, Miao Xu, Zhenzhe Zheng, Chuan Yu, Han Li, Jian Xu, Kun Gai:
Dynamic Knapsack Optimization Towards Efficient Multi-Channel Sequential Advertising. CoRR abs/2006.16312 (2020)
2010 – 2019
- 2019
- [c9]Xiaotian Hao, Weixun Wang, Jianye Hao, Yaodong Yang:
Independent Generative Adversarial Self-Imitation Learning in Cooperative Multiagent Systems. AAMAS 2019: 1315-1323 - [c8]Yaodong Yang, Jianye Hao, Yan Zheng, Xiaotian Hao, Bofeng Fu:
Large-Scale Home Energy Management Using Entropy-Based Collective Multiagent Reinforcement Learning Framework. AAMAS 2019: 2285-2287 - [c7]Leilei Liu, Yi Ma, Xianglei Zhu, Yaodong Yang, Xiaotian Hao, Li Wang, Jiajie Peng:
Integrating Sequence and Network Information to Enhance Protein-Protein Interaction Prediction Using Graph Convolutional Networks. BIBM 2019: 1762-1768 - [c6]Ji Cheng, Guimu Guo, Da Yan, Xiaotian Hao, Wilfred Ng:
EasyRain: A User-Friendly Platform for Comparing Precipitation Nowcasting Models. IEEE BigData 2019: 6019-6021 - [c5]Weixun Wang, Junqi Jin, Jianye Hao, Chunjie Chen, Chuan Yu, Weinan Zhang, Jun Wang, Xiaotian Hao, Yixi Wang, Han Li, Jian Xu, Kun Gai:
Learning Adaptive Display Exposure for Real-Time Advertising. CIKM 2019: 2595-2603 - [c4]Ji Cheng, Da Yan, Xiaotian Hao, Wilfred Ng:
Mining Order-Preserving Submatrices Under Data Uncertainty: A Possible-World Approach. ICDE 2019: 1154-1165 - [i3]Weixun Wang, Tianpei Yang, Yong Liu, Jianye Hao, Xiaotian Hao, Yujing Hu, Yingfeng Chen, Changjie Fan, Yang Gao:
Action Semantics Network: Considering the Effects of Actions in Multiagent Systems. CoRR abs/1907.11461 (2019) - [i2]Weixun Wang, Tianpei Yang, Yong Liu, Jianye Hao, Xiaotian Hao, Yujing Hu, Yingfeng Chen, Changjie Fan, Yang Gao:
From Few to More: Large-scale Dynamic Multiagent Curriculum Learning. CoRR abs/1909.02790 (2019) - [i1]Xiaotian Hao, Weixun Wang, Jianye Hao, Yaodong Yang:
Independent Generative Adversarial Self-Imitation Learning in Cooperative Multiagent Systems. CoRR abs/1909.11468 (2019) - 2018
- [j1]Xiaotian Hao, Jianye Hao, Wang Li, Hanxu Hou:
Effective norm emergence in cell systems under limited communication. BMC Bioinform. 19-S(5): 23-35 (2018) - 2017
- [c3]Xiaotian Hao, Jianye Hao, Wang Li:
Effective norm emergence in cell systems under limited communication. BIBM 2017: 1670-1673 - [c2]Xiaotian Hao, Ji Cheng, Jan Vosecky, Wilfred Ng:
Towards a Query-Less News Search Framework on Twitter. DASFAA (2) 2017: 137-152 - 2014
- [c1]Kai Xing, Di Jiang, Wilfred Ng, Xiaotian Hao:
ADI: Towards a Framework of App Developer Inspection. DASFAA (2) 2014: 266-280
Coauthor Index
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