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Hangyu Mao
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2020 – today
- 2023
- [j5]Bin He
, Hangyu Mao, Tengyu Li, Jing-Long Xiao:
A closed-loop digital twin modeling method integrated with carbon footprint analysis. Comput. Ind. Eng. 182: 109389 (2023) - [j4]Bin He, Hangyu Mao:
Digital Twin-Driven Product Sustainable Design for Low Carbon Footprint. J. Comput. Inf. Sci. Eng. 23(6) (2023) - [c20]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 - [c19]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 - [c18]Ming Yan, Junjie Chen, Hangyu Mao, Jiajun Jiang, Jianye Hao, Xingjian Li, Zhao Tian, Zhichao Chen, Dong Li, Zhangkong Xian, Yanwei Guo, Wulong Liu, Bin Wang, Yuefeng Sun, Yongshun Cui:
Achieving Last-Mile Functional Coverage in Testing Chip Design Software Implementations. ICSE-SEIP 2023: 343-354 - [c17]Mingzhe Xing
, Hangyu Mao
, Shenglin Yin
, Lichen Pan
, Zhengchao Zhang
, Zhen Xiao
, Jieyi Long
:
A Dual-Agent Scheduler for Distributed Deep Learning Jobs on Public Cloud via Reinforcement Learning. KDD 2023: 2776-2788 - [i17]Bin Zhang, Hangyu Mao, Lijuan Li, Zhiwei Xu, Dapeng Li, Rui Zhao, Guoliang Fan:
Stackelberg Decision Transformer for Asynchronous Action Coordination in Multi-Agent Systems. CoRR abs/2305.07856 (2023) - [i16]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) - [i15]Jingqing Ruan, Yihong Chen, Bin Zhang, Zhiwei Xu, Tianpeng Bao, Guoqing Du, Shiwei Shi, Hangyu Mao, Xingyu Zeng, Rui Zhao:
TPTU: Task Planning and Tool Usage of Large Language Model-based AI Agents. CoRR abs/2308.03427 (2023) - [i14]Guanghu Sui, Zhishuai Li, Ziyue Li, Sun Yang, Jingqing Ruan, Hangyu Mao, Rui Zhao:
Reboost Large Language Model-based Text-to-SQL, Text-to-Python, and Text-to-Function - with Real Applications in Traffic Domain. CoRR abs/2310.18752 (2023) - [i13]Yilun Kong, Jingqing Ruan, Yihong Chen, Bin Zhang, Tianpeng Bao, Shiwei Shi, Guoqing Du, Xiaoru Hu, Hangyu Mao, Ziyue Li, Xingyu Zeng, Rui Zhao:
TPTU-v2: Boosting Task Planning and Tool Usage of Large Language Model-based Agents in Real-world Systems. CoRR abs/2311.11315 (2023) - 2022
- [j3]Xianjie Zhang, Yu Liu, Hangyu Mao, Chao Yu:
Common belief multi-agent reinforcement learning based on variational recurrent models. Neurocomputing 513: 341-350 (2022) - [c16]Hongyao Tang, Zhaopeng Meng, Jianye Hao, Chen Chen, Daniel Graves, Dong Li, Changmin Yu, Hangyu Mao, Wulong Liu, Yaodong Yang, Wenyuan Tao, Li Wang:
What about Inputting Policy in Value Function: Policy Representation and Policy-Extended Value Function Approximator. AAAI 2022: 8441-8449 - [c15]Wenhan Huang, Kai Li, Kun Shao, Tianze Zhou, Jun Luo, Dongge Wang, Hangyu Mao, Jianye Hao, Jun Wang, Xiaotie Deng:
Multiagent Q-learning with Sub-Team Coordination. AAMAS 2022: 1630-1632 - [c14]Long Liu, Bin He
, Dong Zhang, Hangyu Mao:
Deep Belief Network-based Prediction for Gear Noise. ICMRE 2022: 50-54 - [c13]Mingzhe Xing, Hangyu Mao, Zhen Xiao:
Fast and Fine-grained Autoscaler for Streaming Jobs with Reinforcement Learning. IJCAI 2022: 564-570 - [c12]Jinpeng Li, Guangyong Chen, Hangyu Mao, Danruo Deng, Dong Li, Jianye Hao, Qi Dou, Pheng-Ann Heng:
Flat-Aware Cross-Stage Distilled Framework for Imbalanced Medical Image Classification. MICCAI (3) 2022: 217-226 - [c11]Lichen Pan, Jun Qian, Wei Xia, Hangyu Mao, Jun Yao, Pengze Li, Zhen Xiao:
Optimizing communication in deep reinforcement learning with XingTian. Middleware 2022: 255-268 - [c10]Wenhan Huang, Kai Li, Kun Shao, Tianze Zhou, Matthew E. Taylor, Jun Luo, Dongge Wang, Hangyu Mao, Jianye Hao, Jun Wang, Xiaotie Deng:
Multiagent Q-learning with Sub-Team Coordination. NeurIPS 2022 - [i12]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) - [i11]Yiqun Chen, Hangyu Mao, Tianle Zhang, Shiguang Wu, Bin Zhang, Jianye Hao, Dong Li, Bin Wang, Hongxing Chang:
PTDE: Personalized Training with Distillated Execution for Multi-Agent Reinforcement Learning. CoRR abs/2210.08872 (2022) - [i10]Hangyu Mao, Rui Zhao, Hao Chen, Jianye Hao, Yiqun Chen, Dong Li, Junge Zhang, Zhen Xiao:
Transformer in Transformer as Backbone for Deep Reinforcement Learning. CoRR abs/2212.14538 (2022) - 2021
- [j2]Xianjie Zhang, Yu Liu, Xiujuan Xu, Qiong Huang, Hangyu Mao, Anil Carie:
Structural relational inference actor-critic for multi-agent reinforcement learning. Neurocomputing 459: 383-394 (2021) - [c9]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 - [c8]Tianpei Yang, Weixun Wang, Hongyao Tang, Jianye Hao, Zhaopeng Meng, Hangyu Mao, Dong Li, Wulong Liu, Yingfeng Chen, Yujing Hu, Changjie Fan, Chengwei Zhang:
An Efficient Transfer Learning Framework for Multiagent Reinforcement Learning. NeurIPS 2021: 17037-17048 - [i9]Tianze Zhou, Fubiao Zhang, Kun Shao, Kai Li, Wenhan Huang, Jun Luo, Weixun Wang, Yaodong Yang, Hangyu Mao, Bin Wang, Dong Li, Wulong Liu, Jianye Hao:
Cooperative Multi-Agent Transfer Learning with Level-Adaptive Credit Assignment. CoRR abs/2106.00517 (2021) - [i8]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) - [i7]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
- [j1]Hangyu Mao, Zhengchao Zhang, Zhen Xiao, Zhibo Gong, Yan Ni:
Learning multi-agent communication with double attentional deep reinforcement learning. Auton. Agents Multi Agent Syst. 34(1): 32 (2020) - [c7]Hangyu Mao, Zhengchao Zhang, Zhen Xiao, Zhibo Gong, Yan Ni:
Learning Agent Communication under Limited Bandwidth by Message Pruning. AAAI 2020: 5142-5149 - [c6]Hangyu Mao, Wulong Liu, Jianye Hao, Jun Luo, Dong Li, Zhengchao Zhang, Jun Wang, Zhen Xiao:
Neighborhood Cognition Consistent Multi-Agent Reinforcement Learning. AAAI 2020: 7219-7226 - [c5]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 - [i6]Hangyu Mao, Zhibo Gong, Zhen Xiao:
Reward Design in Cooperative Multi-agent Reinforcement Learning for Packet Routing. CoRR abs/2003.03433 (2020)
2010 – 2019
- 2019
- [c4]Hangyu Mao, Zhengchao Zhang, Zhen Xiao, Zhibo Gong:
Modelling the Dynamic Joint Policy of Teammates with Attention Multi-agent DDPG. AAMAS 2019: 1108-1116 - [i5]Hangyu Mao, Zhibo Gong, Zhengchao Zhang, Zhen Xiao, Yan Ni:
Learning Multi-agent Communication under Limited-bandwidth Restriction for Internet Packet Routing. CoRR abs/1903.05561 (2019) - [i4]Hangyu Mao, Wulong Liu, Jianye Hao, Jun Luo, Dong Li, Zhengchao Zhang, Jun Wang, Zhen Xiao:
Neighborhood Cognition Consistent Multi-Agent Reinforcement Learning. CoRR abs/1912.01160 (2019) - [i3]Hangyu Mao, Zhengchao Zhang, Zhen Xiao, Zhibo Gong, Yan Ni:
Learning Agent Communication under Limited Bandwidth by Message Pruning. CoRR abs/1912.05304 (2019) - 2018
- [c3]Hangyu Mao, Yang Xiao, Yuan Wang, Jiakang Wang, Zhen Xiao:
Topic-Specific Retweet Count Ranking for Weibo. PAKDD (3) 2018: 625-637 - [i2]Hangyu Mao, Zhengchao Zhang, Zhen Xiao, Zhibo Gong:
Modelling the Dynamic Joint Policy of Teammates with Attention Multi-agent DDPG. CoRR abs/1811.07029 (2018) - 2017
- [c2]Yuan Wang, Hangyu Mao, Zhen Xiao:
Identifying Influential Users' Professions via the Microblogs They Forward. SocInf@IJCAI 2017: 33-44 - [i1]Hangyu Mao, Zhibo Gong, Yan Ni, Xiangyu Liu, Quanbin Wang, Weichen Ke, Chao Ma, Yiping Song, Zhen Xiao:
ACCNet: Actor-Coordinator-Critic Net for "Learning-to-Communicate" with Deep Multi-agent Reinforcement Learning. CoRR abs/1706.03235 (2017) - 2016
- [c1]Yang Xiao, Yuan Wang, Hangyu Mao, Zhen Xiao:
Predicting Restaurant Consumption Level through Social Media Footprints. COLING 2016: 3328-3338
Coauthor Index

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last updated on 2023-11-24 18:53 CET by the dblp team
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