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Diversity is Strength: Mastering Football Full Game with Interactive Reinforcement Learning of Multiple AIs

Autor: Sun, Chenglu, Shen, Shuo, Xu, Sijia, Zhang, Weidong

Training AI with strong and rich strategies in multi-agent environments remains an important research topic in Deep Reinforcement Learning (DRL). The AI's strength is closely related to its diversity of strategies, and this relationship can guide us

Externí odkaz: http://arxiv.org/abs/2306.15903

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Akademický článek

Design of a sparse convolutional cardiac arrhythmia classification accelerator for wearable devices(针对可穿戴设备的稀疏化卷积心律失常分类加速器设计)

Autor: 徐轶凡(XU Yifan), 申烁(SHEN Shuo), 林昊(LIN Hao), 吴中行(WU Zhongxing), 刘昊(LIU Hao)

Publikováno v: Zhejiang Daxue xuebao. Lixue ban, Vol 51, Iss 4, Pp 492-500 (2024)

In recent years, convolutional neural networks (CNN) have gained significant attention in the research of electrocardiogram (ECG) signal diagnosis due to their excellent detection and recognition capabilities. However, the large size of parameters an

Externí odkaz: https://doaj.org/article/64c5da6d86a7456abcc31484c55f461d

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Spatial data sharing with secure multi-party computation for exploratory spatial data analysis

Autor: Shen, Shuo, Zhu, Xinyan, Ma, Yanlei, Xiang, XIe, Lilin, Sun, Hongjun, Xie, Rui, An

Spatial data sharing plays a significant role in opening data research and promoting government agency transparency. However, valuable spatial data, like high-precision geographic information and personal traffic records, cannot be made public becaus

Externí odkaz: http://arxiv.org/abs/2207.13069

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