Zobrazeno 1 - 10
of 451
pro vyhledávání: '"Meng, Linghui"'
Enhancing automatic speech recognition (ASR) performance by leveraging additional multimodal information has shown promising results in previous studies. However, most of these works have primarily focused on utilizing visual cues derived from human
Externí odkaz:
http://arxiv.org/abs/2305.19972
Adaptive human-agent and agent-agent cooperation are becoming more and more critical in the research area of multi-agent reinforcement learning (MARL), where remarked progress has been made with the help of deep neural networks. However, many establi
Externí odkaz:
http://arxiv.org/abs/2305.05898
Autor:
Yu, Feng1,2 (AUTHOR), Meng, Linghui1,2 (AUTHOR) linghuimeng2023@163.com, Li, Xianxian1,2 (AUTHOR), Jiang, Daicen3 (AUTHOR), Zhu, Weidong1,2 (AUTHOR), Zeng, Zhihua4 (AUTHOR)
Publikováno v:
Mathematics (2227-7390). Sep2024, Vol. 12 Issue 18, p2906. 25p.
Autor:
Lu, Yile, Yuan, Yu, Liang, Tianyue, Jia, Haowei, Meng, Linghui, Zhang, Xinren, Zhang, Shuo, Wen, Bohao, Feng, Ziheng, Yin, Tao, Guan, Peiyuan, Zhou, Lu, Zhou, Yingze, Chu, Dewei
Publikováno v:
In Chemical Engineering Journal 15 October 2024 498
Autor:
Meng, Linghui, Zhao, Chen, Zhang, Xiang, Guo, Runxuan, Zheng, Yafei, Chu, Hongyu, Fu, Huifen, Wang, Peng, Wang, Chong-Chen
Publikováno v:
In Nano Energy September 2024 128 Part A
Publikováno v:
In Colloids and Surfaces A: Physicochemical and Engineering Aspects 5 August 2024 694
Autor:
Ruan, Jingqing, Du, Yali, Xiong, Xuantang, Xing, Dengpeng, Li, Xiyun, Meng, Linghui, Zhang, Haifeng, Wang, Jun, Xu, Bo
Many real-world scenarios involve a team of agents that have to coordinate their policies to achieve a shared goal. Previous studies mainly focus on decentralized control to maximize a common reward and barely consider the coordination among control
Externí odkaz:
http://arxiv.org/abs/2201.06257
Autor:
Meng, Linghui, Wen, Muning, Yang, Yaodong, Le, Chenyang, Li, Xiyun, Zhang, Weinan, Wen, Ying, Zhang, Haifeng, Wang, Jun, Xu, Bo
Offline reinforcement learning leverages previously-collected offline datasets to learn optimal policies with no necessity to access the real environment. Such a paradigm is also desirable for multi-agent reinforcement learning (MARL) tasks, given th
Externí odkaz:
http://arxiv.org/abs/2112.02845
Autor:
Meng, Linghui, Zhou, Lu, Liu, Chao, Jia, Haowei, Lu, Yile, Ji, Dali, Liang, Tianyue, Yuan, Yu, Zhang, Xinren, Zhu, Yanzhe, Jiang, Yue, Guan, Peiyuan, Zhou, Yingze, Zhang, Qi, Wan, Tao, Li, Mengyao, Li, Zhi, Joshi, Rakesh, Han, Zhaojun, Chu, Dewei
Publikováno v:
In Journal of Colloid And Interface Science 15 November 2024 674:972-981
Autor:
Fan, Wuyang, Meng, Linghui, Sun, Shaolian, Wei, Haoming, Kong, Qingkun, Wu, Yangqing, Cao, Bingqiang
Publikováno v:
In Ceramics International 1 November 2024 50(21) Part A:41802-41809