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Event-Triggered Communication Network With Limited-Bandwidth Constraint for Multi-Agent Reinforcement Learning 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 13
作者:  Hu, Guangzheng;  Zhu, Yuanheng;  Zhao, Dongbin;  Zhao, Mengchen;  Hao, Jianye
收藏  |  浏览/下载：215/0  |  提交时间：2022/01/27
Bandwidth  Protocols  Reinforcement learning  Task analysis  Optimization  Communication networks  Multi-agent systems  Event trigger  limited bandwidth  multi-agent communication  multi-agent reinforcement learning (MARL)  
A deep learning-based radiomic nomogram for prognosis and treatment decision in advanced nasopharyngeal carcinoma: A multicentre study 期刊论文
EBIOMEDICINE, 2021, 卷号: 70, 页码: 10
作者:  Zhong, Lianzhen;  Dong, Di;  Fang, Xueliang;  Zhang, Fan;  Zhang, Ning;  Zhang, Liwen;  Fang, Mengjie;  Jiang, Wei;  Liang, Shaobo;  Li, Cong;  Liu, Yujia;  Zhao, Xun;  Cao, Runnan;  Shan, Hong;  Hu, Zhenhua;  Ma, Jun;  Tang, Linglong;  Tian, Jie
Adobe PDF(3679Kb)  |  收藏  |  浏览/下载：377/70  |  提交时间：2021/11/03
Multi-task deep learning  Radiomic nomogram  Survival analysis  Treatment decision  Advanced nasopharyngeal carcinoma